Wind Power Prediction Considering Nonlinear Atmospheric Disturbances
Directory of Open Access Journals (Sweden)
Yagang Zhang
2015-01-01
Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.
Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance
Directory of Open Access Journals (Sweden)
ZHANG, Y.
2017-08-01
Full Text Available Due to the sustainable and pollution-free characteristics, wind energy has been one of the fastest growing renewable energy sources. However, the intermittent and random fluctuation of wind speed presents many challenges for reliable wind power integration and normal operation of wind farm. Accurate wind speed prediction is the key to ensure the safe operation of power system and to develop wind energy resources. Therefore, this paper has presented a wavelet time series wind speed prediction model based on Lorenz disturbance. Therefore, in this paper, combined with the atmospheric dynamical system, a wavelet-time series improved wind speed prediction model based on Lorenz disturbance is proposed and the wind turbines of different climate types in Spain and China are used to simulate the disturbances of Lorenz equations with different initial values. The prediction results show that the improved model can effectively correct the preliminary prediction of wind speed, improving the prediction. In a word, the research work in this paper will be helpful to arrange the electric power dispatching plan and ensure the normal operation of the wind farm.
Repetitive model predictive approach to individual pitch control of wind turbines
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Stoustrup, Jakob; Odgaard, Peter Fogh
2011-01-01
prediction. As a consequence, individual pitch feed-forward control action is generated by the controller, taking ”future” wind disturbance into account. Information about the estimated wind spatial distribution one blade experience can be used in the prediction model to better control the next passing blade......Wind turbines are inherently exposed to nonuniform wind fields with of wind shear, tower shadow, and possible wake contributions. Asymmetrical aerodynamic rotor loads are a consequence of such periodic, repetitive wind disturbances experienced by the blades. A controller may estimate and use...... this peculiar disturbance pattern to better attenuate loads and regulate power by controlling the blade pitch angles individually. A novel model predictive (MPC) approach for individual pitch control of wind turbines is proposed in this paper. A repetitive wind disturbance model is incorporated into the MPC...
The influence of experimental wind disturbance on forest fuels and fire characteristics
Jeffery B. Cannon; Joseph J. O' Brien; Louise Loudermilk; Matthew Dickinson; Chris J. Peterson
2014-01-01
Current theory in disturbance ecology predicts that extreme disturbances in rapid succession can lead to dramatic changes in species composition or ecosystem processes due to interactions among disturbances. However, the extent to which less catastrophic, yet chronic, disturbances such as wind damage and fire interact is not well studied. In this study, we simulated...
Partial analysis of wind power limit for large disturbance using fixed speed wind turbine
International Nuclear Information System (INIS)
Santos Fuentefria, Ariel; Cairo Rodriguez, Daniel; Boza Valerino, Juan Gualberto
2014-01-01
The amount of wind power that allow an electric network without losing his stability as known as wind power limit. The wind power limit fundamentally depends on the wind turbine technology and the weakness level of the system. To know the system behaviors in dynamic performance having into account the worst disturbance is a very important matter, a short circuit in one of the most power transference line or the loss of a large generation unit was a large disturbance that can affect system stability. The wind power limit may change with the nature of the disturbance. To know the wind power limit considering this conditions allow use the wind at maximum level. In the present paper the behavior of fixed speed wind turbine for different fault types is analyzed, at those conditions, the wind power is increasing until the system become voltage unstable. For the analysis the IEEE 14 Bus Test Case is used. The Power System Analysis Toolbox (PSAT) package is used for the simulation. (author)
Directory of Open Access Journals (Sweden)
Chengwu Li
2016-05-01
Full Text Available Wind energy is known as one of the most efficient clean renewable energy sources and has attracted extensive research interests in both academic and industry fields. In this study, the effects of turbulent wind and voltage disturbance on a wind turbine drivetrain are analyzed, and a wind turbine drivetrain dynamic model combined with the electric model of a doubly fed induction generator is established. The proposed model is able to account for the dynamic interaction between turbulent wind, voltage disturbance, and mechanical system. Also, the effects of time-varying meshing stiffness, transmission error, and bearing stiffness are included in the mechanical part of the coupled dynamic model. From the resultant model, system modes are computed. In addition, by considering the actual control strategies in the simulation process, the effects of turbulent wind and voltage disturbance on the geared rotor system are analyzed. The computational results show that the turbulent wind and voltage disturbance can cause adverse effects on the wind turbine drivetrain, especially the gearbox. A series of parametric studies are also performed to understand the influences of generator and gearbox parameters on the drivetrain system dynamics. Finally, the appropriate generator parameters having a positive effect on the gearbox in alleviating the extreme loads and the modeling approach for investigating the transient performance of generator are discussed.
Wind power prediction based on genetic neural network
Zhang, Suhan
2017-04-01
The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.
International Nuclear Information System (INIS)
Melicio, R.; Mendes, V.M.F.; Catalao, J.P.S.
2011-01-01
As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn.
Energy Technology Data Exchange (ETDEWEB)
Melicio, R. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)
2011-04-15
As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (author)
Prediction models for wind speed at turbine locations in a wind farm
DEFF Research Database (Denmark)
Knudsen, Torben; Bak, Thomas; Soltani, Mohsen
2011-01-01
In wind farms, individual turbines disturb the wind field by generating wakes that influence other turbines in the farm. From a control point of view, there is an interest in dynamic optimization of the balance between fatigue and production, and an understanding of the relationship between turbines...... on standard turbine measurements such as rotor speed and power produced, an effective wind speed, which represents the wind field averaged over the rotor disc, is derived. The effective wind speed estimator is based on a continuous–discrete extended Kalman filter that takes advantage of nonlinear time varying...... on the result related to effective wind speed, it is possible to predict wind speeds at neighboring turbines, with a separation of over 700 m, up to 1 min ahead reducing the error by 30% compared with a persistence method. The methodological results are demonstrated on data from an off-shore wind farm...
Nonlinear Feedforward Control for Wind Disturbance Rejection on Autonomous Helicopter
DEFF Research Database (Denmark)
Bisgaard, Morten; la Cour-Harbo, Anders; A. Danapalasingam, Kumeresan
2010-01-01
for the purpose. The model is inverted for the calculation of rotor collective and cyclic pitch angles given the wind disturbance. The control strategy is then applied on a small helicopter in a controlled wind environment and flight tests demonstrates the effectiveness and advantage of the feedforward controller.......This paper presents the design and verification of a model based nonlinear feedforward controller for wind disturbance rejection on autonomous helicopters. The feedforward control is based on a helicopter model that is derived using a number of carefully chosen simplifications to make it suitable...
Visitor attitudes towards fire and wind disturbances in wilderness
Robert G. Dvorak; Erin D. Small
2011-01-01
This study examines visitor attitudes across the Boundary Waters Canoe Area Wilderness regarding the effects of natural disturbances on visitor planning and wilderness conditions. Visitors were intercepted at entry points and permit distribution locations during 2007. Results suggest that respondents were aware of recent wind and fire disturbances. Few respondents...
Seidl, Rupert; Rammer, Werner
2017-07-01
Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown. Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances. We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination. iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime. Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.
Blanch, E.; Altadill, D.
2009-04-01
Geomagnetic storms disturb the quiet behaviour of the ionosphere, its electron density and the electron density peak height, hmF2. Many works have been done to predict the variations of the electron density but few efforts have been dedicated to predict the variations the hmF2 under disturbed helio-geomagnetic conditions. We present the results of the analyses of the F2 layer peak height disturbances occurred during intense geomagnetic storms for one solar cycle. The results systematically show a significant peak height increase about 2 hours after the beginning of the main phase of the geomagnetic storm, independently of both the local time position of the station at the onset of the storm and the intensity of the storm. An additional uplift is observed in the post sunset sector. The duration of the uplift and the height increase are dependent of the intensity of the geomagnetic storm, the season and the local time position of the station at the onset of the storm. An empirical model has been developed to predict the electron density peak height disturbances in response to solar wind conditions and local time which can be used for nowcasting and forecasting the hmF2 disturbances for the middle latitude ionosphere. This being an important output for EURIPOS project operational purposes.
Disturbance Accommodating Adaptive Control with Application to Wind Turbines
Frost, Susan
2012-01-01
Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.
Modeling of Driver Steering Operations in Lateral Wind Disturbances toward Driver Assistance System
Kurata, Yoshinori; Wada, Takahiro; Kamiji, Norimasa; Doi, Shun'ichi
Disturbances decrease vehicle stability and increase driver's mental and physical workload. Especially unexpected disturbances such as lateral winds have severe effect on vehicle stability and driver's workload. This study aims at building a driver model of steering operations in lateral wind toward developing effective driver assistance system. First, the relationship between the driver's lateral motion and its reactive quick steering behavior is investigated using driving simulator with lateral 1dof motion. In the experiments, four different wind patterns are displayed by the simulator. As the results, strong correlation was found between the driver's head lateral jerk by the lateral disturbance and the angular acceleration of the steering wheel. Then, we build a mathematical model of driver's steering model from lateral disturbance input to steering torque of the reactive quick feed-forward steering based on the experimental results. Finally, validity of the proposed model is shown by comparing the steering torque of experimental results and that of simulation results.
Bakker, R H; Pedersen, E; van den Berg, G P; Stewart, R E; Lok, W; Bouma, J
2012-05-15
The present government in the Netherlands intends to realize a substantial growth of wind energy before 2020, both onshore and offshore. Wind turbines, when positioned in the neighborhood of residents may cause visual annoyance and noise annoyance. Studies on other environmental sound sources, such as railway, road traffic, industry and aircraft noise show that (long-term) exposure to sound can have negative effects other than annoyance from noise. This study aims to elucidate the relation between exposure to the sound of wind turbines and annoyance, self-reported sleep disturbance and psychological distress of people that live in their vicinity. Data were gathered by questionnaire that was sent by mail to a representative sample of residents of the Netherlands living in the vicinity of wind turbines A dose-response relationship was found between immission levels of wind turbine sound and selfreported noise annoyance. Sound exposure was also related to sleep disturbance and psychological distress among those who reported that they could hear the sound, however not directly but with noise annoyance acting as a mediator. Respondents living in areas with other background sounds were less affected than respondents in quiet areas. People living in the vicinity of wind turbines are at risk of being annoyed by the noise, an adverse effect in itself. Noise annoyance in turn could lead to sleep disturbance and psychological distress. No direct effects of wind turbine noise on sleep disturbance or psychological stress has been demonstrated, which means that residents, who do not hear the sound, or do not feel disturbed, are not adversely affected. Copyright © 2012 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Verma, P L; Singh, Puspraj; Singh, Preetam
2014-01-01
Coronal Mass Ejections (CMEs) are the drastic solar events in which huge amount of solar plasma materials are ejected into the heliosphere from the sun and are mainly responsible to generate large disturbances in solar wind plasma parameters and geomagnetic storms in geomagnetic field. We have studied geomagnetic storms, (Dst ≤-75 nT) observed during the period of 1997-2007 with Coronal Mass Ejections and disturbances in solar wind plasma parameters (solar wind temperature, velocity, density and interplanetary magnetic field) .We have inferred that most of the geomagnetic storms are associated with halo and partial halo Coronal Mass Ejections (CMEs).The association rate of halo and partial halo coronal mass ejections are found 72.37 % and 27.63 % respectively. Further we have concluded that geomagnetic storms are closely associated with the disturbances in solar wind plasma parameters. We have determined positive co-relation between magnitudes of geomagnetic storms and magnitude of jump in solar wind plasma temperature, jump in solar wind plasma density, jump in solar wind plasma velocity and jump in average interplanetary magnetic field with co-relation co-efficient 0 .35 between magnitude of geomagnetic storms and magnitude of jump in solar wind plasma temperature, 0.19 between magnitude of geomagnetic storms and magnitude of jump in solar wind density, 0.34 between magnitude of geomagnetic storms and magnitude of jump in solar wind plasma velocity, 0.66 between magnitude of geomagnetic storms and magnitude of jump in average interplanetary magnetic field respectively. We have concluded that geomagnetic storms are mainly caused by Coronal Mass Ejections and disturbances in solar wind plasma parameters that they generate.
Substorm-related thermospheric density and wind disturbances derived from CHAMP observations
Directory of Open Access Journals (Sweden)
P. Ritter
2010-06-01
Full Text Available The input of energy and momentum from the magnetosphere is most efficiently coupled into the high latitude ionosphere-thermosphere. The phenomenon we are focusing on here is the magnetospheric substorm. This paper presents substorm related observations of the thermosphere derived from the CHAMP satellite. With its sensitive accelerometer the satellite can measure the air density and zonal winds. Based on a large number of substorm events the average high and low latitude thermospheric response to substorm onsets was deduced. During magnetic substorms the thermospheric density is enhanced first at high latitudes. Then the disturbance travels at an average speed of 650 m/s to lower latitudes, and 3–4 h later the bulge reaches the equator on the night side. Under the influence of the Coriolis force the travelling atmospheric disturbance (TAD is deflected westward. In accordance with present-day atmospheric models the disturbance zonal wind velocities during substorms are close to zero near the equator before midnight and attain moderate westward velocities after midnight. In general, the wind system is only weakly perturbed (Δvy<20 m/s by substorms.
Model predictive control of PMSG-based wind turbines for frequency regulation in an isolated grid
DEFF Research Database (Denmark)
Wang, Haixin; Yang, Junyou; Ma, Yiming
2017-01-01
This paper proposes a frequency regulation strategy applied to wind turbine generators (WTGs) in an isolated grid. In order to complement active power shortage caused by sudden load or wind speed change, an improved deloading method is proposed to solve inconsistent regulation capabilities...... in different speed regions and provide WTGs a certain capacity of power reserves. Considering the torque compensation may bring about power oscillation, speed reference of conventional pitch control system should be reset. Moreover, to suppress disturbances of load and wind speed as well as overcome dependence...... on system parameters, a model predictive controller (MPC) of wind farm is designed to generate torque compensation for each deloaded WTG. The key feature of this strategy is that each WTG reacts to grid disturbances in different ways, which depends on generator speeds. Hardware-in-the-loop simulation...
Abbasi, Milad; Monazzam, Mohammad Reza; Akbarzadeh, Arash; Zakerian, Seyyed Abolfazl; Ebrahimi, Mohammad Hossein
2015-01-01
The wind turbine's sound seems to have a proportional effect on health of people living near to wind farms. This study aimed to investigate the effect of noise emitted from wind turbines on general health, sleep and annoyance among workers of manjil wind farm, Iran. A total number of 53 workers took part in this study. Based on the type of job, they were categorized into three groups of maintenance, security and office staff. The persons' exposure at each job-related group was measured by eight-hour equivalent sound level (LAeq, 8 h). A Noise annoyance scale, Epworth sleepiness scale and 28-item general health questionnaire was used for gathering data from workers. The data were analyzed through Multivariate Analysis of variance (MANOVA) test, Pillai's Trace test, Paired comparisons analysis and Multivariate regression test were used in the R software. The results showed that, response variables (annoyance, sleep disturbance and health) were significantly different between job groups. The results also indicated that sleep disturbance as well as noise exposure had a significant effect on general health. Noise annoyance and distance from wind turbines could significantly explain about 44.5 and 34.2 % of the variance in sleep disturbance and worker's general health, respectively. General health was significantly different in different age groups while age had no significant impact on sleep disturbance. The results were reverse for distance because it had no significant impact on health, but sleep disturbance was significantly affected. We came to this conclusion that wind turbines noise can directly impact on annoyance, sleep and health. This type of energy generation can have potential health risks for wind farm workers. However, further research is needed to confirm the results of this study.
International Nuclear Information System (INIS)
Tang, Yanmei; Bai, Yan; Huang, Congzhi; Du, Bin
2015-01-01
Highlights: • A disturbance rejection solution to the load frequency control issue is proposed. • Several power systems with wind energy conversation system have been tested. • A tuning algorithm of the controller parameters was proposed. • The performance of the proposed approach is better than traditional controllers. - Abstract: A new grid load frequency control approach is proposed for the doubly fed induction generator based wind power plants. The load frequency control issue in a power system is undergoing fundamental changes due to the rapidly growing amount of wind energy conversation system, and concentrating on maintaining generation-load balance and disturbance rejection. The prominent feature of the linear active disturbance rejection control approach is that the total disturbance can be estimated and then eliminated in real time. And thus, it is a feasible solution to deal with the load frequency control issue. In this paper, the application of the linear active disturbance rejection control approach in the load frequency control issue for a complex power system with wind energy conversation system based on doubly fed induction generator is investigated. The load frequency control issue is formulated as a decentralized multi-objective optimization control problem, the solution to which is solved by the hybrid particle swarm optimization technique. To show the effectiveness of the proposed control scheme, the robust performance testing based on Monte-Carlo approach is carried out. The performance superiority of the system with the proposed linear active disturbance rejection control approach over that with the traditional proportional integral and fuzzy-proportional integral-based controllers is validated by the simulation results
A dynamic system to forecast ionospheric storm disturbances based on solar wind conditions
Directory of Open Access Journals (Sweden)
L. R. Cander
2005-06-01
Full Text Available For the reliable performance of technologically advanced radio communications systems under geomagnetically disturbed conditions, the forecast and modelling of the ionospheric response during storms is a high priority. The ionospheric storm forecasting models that are currently in operation have shown a high degree of reliability during quiet conditions, but they have proved inadequate during storm events. To improve their prediction accuracy, we have to take advantage of the deeper understanding in ionospheric storm dynamics that is currently available, indicating a correlation between the Interplanetary Magnetic Field (IMF disturbances and the qualitative signature of ionospheric storm disturbances at middle latitude stations. In this paper we analyse observations of the foF2 critical frequency parameter from one mid-latitude European ionospheric station (Chilton in conjunction with observations of IMF parameters (total magnitude, Bt and Bz-IMF component from the ACE spacecraft mission for eight storm events. The determination of the time delay in the ionospheric response to the interplanetary medium disturbances leads to significant results concerning the forecast of the ionospheric storms onset and their development during the first 24 h. In this way the real-time ACE observations of the solar wind parameters may be used in the development of a real-time dynamic ionospheric storm model with adequate accuracy.
Extended onshore control of a floating wind turbine with wave disturbance reduction
DEFF Research Database (Denmark)
Christiansen, S.; Knudsen, T.; Bak, Thomas
2014-01-01
Reaching for higher wind resources floating wind turbines are being investigated. Wave induced loads significantly increase for floating wind turbines, and applying conventional onshore control strategies to floating wind turbines has been shown to impose negative damped oscillations in fore......-aft due to the low natural frequency of the floating structure. We suggest a control loop extension of the onshore controller which stabilizes the system and reduces the wave disturbance. The result is improved performance in power fluctuations, blade pitch activity, and platform oscillations...
Parameterized Disturbance Observer Based Controller to Reduce Cyclic Loads of Wind Turbine
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Raja M. Imran
2018-05-01
Full Text Available This paper is concerned with bump-less transfer of parameterized disturbance observer based controller with individual pitch control strategy to reduce cyclic loads of wind turbine in full load operation. Cyclic loads are generated due to wind shear and tower shadow effects. Multivariable disturbance observer based linear controllers are designed with objective to reduce output power fluctuation, tower oscillation and drive-train torsion using optimal control theory. Linear parameterized controllers are designed by using a smooth scheduling mechanism between the controllers. The proposed parameterized controller with individual pitch was tested on nonlinear Fatigue, Aerodynamics, Structures, and Turbulence (FAST code model of National Renewable Energy Laboratory (NREL’s 5 MW wind turbine. The closed-loop system performance was assessed by comparing the simulation results of proposed controller with a fixed gain and parameterized controller with collective pitch for full load operation of wind turbine. Simulations are performed with step wind to see the behavior of the system with wind shear and tower shadow effects. Then, turbulent wind is applied to see the smooth transition of the controllers. It can be concluded from the results that the proposed parameterized control shows smooth transition from one controller to another controller. Moreover, 3p and 6p harmonics are well mitigated as compared to fixed gain DOBC and parameterized DOBC with collective pitch.
Levy, R.; Mcginness, H.
1976-01-01
Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.
Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.
2013-01-01
A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.
Control of variable speed variable pitch wind turbine based on a disturbance observer
Ren, Haijun; Lei, Xin
2017-11-01
In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.
Schwartz, Naomi B; Uriarte, María; DeFries, Ruth; Bedka, Kristopher M; Fernandes, Katia; Gutiérrez-Vélez, Victor; Pinedo-Vasquez, Miguel A
2017-09-01
Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds on second-growth forests in fragmented landscapes, though these ecosystems are often located in mosaics of forest, pasture, cropland, and other land cover types. Indirect evidence suggests that fragmentation increases risk of wind damage in tropical forests, but no studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass. We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 ha of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches. Damage was also more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation. These results illustrate the importance of considering landscape context in planning tropical forest restoration and natural regeneration projects. Assessments of long-term carbon sequestration potential need to consider spatial variation in disturbance exposure. Where risk of extreme winds is high, minimizing fragmentation and isolation could increase
Model Predictive Control for Load Frequency Control with Wind Turbines
Directory of Open Access Journals (Sweden)
Yi Zhang
2015-01-01
Full Text Available Reliable load frequency (LFC control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.
Microgravity Disturbance Predictions in the Combustion Integrated Rack
Just, M.; Grodsinsky, Carlos M.
2002-01-01
This paper will focus on the approach used to characterize microgravity disturbances in the Combustion Integrated Rack (CIR), currently scheduled for launch to the International Space Station (ISS) in 2005. Microgravity experiments contained within the CIR are extremely sensitive to vibratory and transient disturbances originating on-board and off-board the rack. Therefore, several techniques are implemented to isolate the critical science locations from external vibration. A combined testing and analysis approach is utilized to predict the resulting microgravity levels at the critical science location. The major topics to be addressed are: 1) CIR Vibration Isolation Approaches, 2) Disturbance Sources and Characterization, 3) Microgravity Predictive Modeling, 4) Science Microgravity Requirements, 6) Microgravity Control, and 7) On-Orbit Disturbance Measurement. The CIR is using the Passive Rack Isolation System (PaRIS) to isolate the rack from offboard rack disturbances. By utilizing this system, CIR is connected to the U.S. Lab module structure by either 13 or 14 umbilical lines and 8 spring / damper isolators. Some on-board CIR disturbers are locally isolated by grommets or wire ropes. CIR's environmental and science on board support equipment such as air circulation fans, pumps, water flow, air flow, solenoid valves, and computer hard drives cause disturbances within the rack. These disturbers along with the rack structure must be characterized to predict whether the on-orbit vibration levels during experimentation exceed the specified science microgravity vibration level requirements. Both vibratory and transient disturbance conditions are addressed. Disturbance levels/analytical inputs are obtained for each individual disturber in a "free floating" condition in the Glenn Research Center (GRC) Microgravity Emissions Lab (MEL). Flight spare hardware is tested on an Orbital Replacement Unit (ORU) basis. Based on test and analysis, maximum disturbance level
Prediction of windings temperature rise in induction motors supplied with distorted voltage
Energy Technology Data Exchange (ETDEWEB)
Gnacinski, P. [Gdynia Maritime University, Department of Ship Electrical Power Engineering, Morska Street 83, 81-225 Gdynia (Poland)
2008-04-15
One of the features of ship power systems is a different level and intensity of disturbances appearing during routine operation - the rms voltage value and frequency deviation, voltage unbalance and waveform voltage distortion. As a result, marine induction machines are exposed to overheating due to the lowered voltage quality. This paper is devoted to windings temperature rise prediction in marine induction cage machines supplied with distorted voltage, which means real voltage conditions. The proposed method of prediction does not require detailed knowledge of the thermal properties of a machine. Although the method was developed for marine induction motors, it is applicable for industry machines supplied with distorted voltage. It can also be generalized and used for estimation of the steady state windings temperature rise of any electrical machinery in various work conditions. (author)
Prediction of windings temperature rise in induction motors supplied with distorted voltage
International Nuclear Information System (INIS)
Gnacinski, P.
2008-01-01
One of the features of ship power systems is a different level and intensity of disturbances appearing during routine operation - the rms voltage value and frequency deviation, voltage unbalance and waveform voltage distortion. As a result, marine induction machines are exposed to overheating due to the lowered voltage quality. This paper is devoted to windings temperature rise prediction in marine induction cage machines supplied with distorted voltage, which means real voltage conditions. The proposed method of prediction does not require detailed knowledge of the thermal properties of a machine. Although the method was developed for marine induction motors, it is applicable for industry machines supplied with distorted voltage. It can also be generalized and used for estimation of the steady state windings temperature rise of any electrical machinery in various work conditions
Predicting geomagnetic storms from solar-wind data using time-delay neural networks
Directory of Open Access Journals (Sweden)
H. Gleisner
1996-07-01
Full Text Available We have used time-delay feed-forward neural networks to compute the geomagnetic-activity index Dst one hour ahead from a temporal sequence of solar-wind data. The input data include solar-wind density n, velocity V and the southward component Bz of the interplanetary magnetic field. Dst is not included in the input data. The networks implement an explicit functional relationship between the solar wind and the geomagnetic disturbance, including both direct and time-delayed non-linear relations. In this study we especially consider the influence of varying the temporal size of the input-data sequence. The networks are trained on data covering 6600 h, and tested on data covering 2100 h. It is found that the initial and main phases of geomagnetic storms are well predicted, almost independent of the length of the input-data sequence. However, to predict the recovery phase, we have to use up to 20 h of solar-wind input data. The recovery phase is mainly governed by the ring-current loss processes, and is very much dependent on the ring-current history, and thus also the solar-wind history. With due consideration of the time history when optimizing the networks, we can reproduce 84% of the Dst variance.
Deterministic prediction of surface wind speed variations
Directory of Open Access Journals (Sweden)
G. V. Drisya
2014-11-01
Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.
International Nuclear Information System (INIS)
Kikvilashvili, G.B.; Sharadze, Z.S.; Mosashvili, N.V.
1988-01-01
Madium-scale travelling ionospheric disturbances (MSTID) in the ionosphere E region in Tbilisi area are investigated by means of spectral analysis of f 0 E s and f b E s variations, synchronously recorded in the three scattered points. The winds at the E s layers formation heights were measured simultaneously by D1 method in one of these points. It is established, that the MSTID motion direction in summer-time E region is controlled by the background thermospheric winds: disturbances mostly more across and against the wind. Tidal winds make the main contribution into the MSTID rate day variations
DEFF Research Database (Denmark)
Imran, Raja Muhammad; Hussain, Dil Muhammad Akbar; Soltani, Mohsen
2015-01-01
scheme to mitigate the effect of 3p flicker on drive train. 5MW wind turbine of the National Renewable Laboratories (NREL) is used as research object and results are simulated in MATLAB/Simulink. We designed the controller based on linearized model of the wind turbine generated for above rated wind speed...... and then tested its performance on the nonlinear model of wind turbine. We have shown a comparison of the results for proportional-integral(PI) and proposed DAC controller tested on nonlinear model of wind turbine. Result shows that our proposed controller shows better mitigation of flicker generated due to 3p......DAC is a linear control technique used to mitigate the effect of disturbance on the plant. It is a superposition of full state feedback and disturbance feedback. This paper presents a control technique based on Disturbance Accommodation Control (DAC) to reduce fatigue on drive train generated...
Model predictive control of trailing edge flaps on a wind turbine blade
Energy Technology Data Exchange (ETDEWEB)
Castaignet, D.B.
2011-11-15
Trailing edge flaps on wind turbine blades have been investigated for several years. Aero-servoelastic simulations carried out with different simulation tools, trailing edge flaps configurations and controller designs proved that trailing edge flaps are a suitable solution for reducing some of the wind turbine fatigue and extreme loads. This potential was confirmed with wind tunnel tests made on blade sections with trailing edge flaps and on a scaled two-bladed wind turbine in a wind tunnel. The work presented in this thesis includes a full-scale test run on a Vestas V27 wind turbine equipped with three trailing edge flaps on one blade, located on DTU's Risoe Campus in Roskilde, Denmark. This thesis is divided into three parts: the controller design, results from simulations, and results from the experiments. The trailing edge flaps controller designed for this project is based on a frequency-weighted model predictive control, tuned in order to target only the flapwise blade root loads at the frequencies contributing the most to blade root fatigue damage (the 1P, 2P and 3P frequencies), and to avoid unnecessary wear and tear of the actuators at high frequencies. A disturbance model consisting in periodic disturbances at the rotor speed harmonic frequencies and a quasi-steady input disturbance is aggregated to an analytical model of a spinning blade with trailing edge flaps. Simulations on a multi-megawatt wind turbine show the potential of the trailing edge flaps to reduce the flapwise blade root fatigue loads by 23%, but also the main shaft and the tower fatigue loads by up to 32%. Extreme loads during normal production also benefit from the trailing edge flaps. At last, the same controller was run on the Vestas V27 wind turbine located at the Risoe Campus of the Technical University of Denmark, in Roskilde, Denmark. One blade of the turbine was equipped with three independent trailing edge flaps. In spite of the failure of several sensors and actuators, the
Conditional prediction intervals of wind power generation
DEFF Research Database (Denmark)
Pinson, Pierre; Kariniotakis, Georges
2010-01-01
A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....
On the Predictability of Hub Height Winds
DEFF Research Database (Denmark)
Draxl, Caroline
Wind energy is a major source of power in over 70 countries across the world, and the worldwide share of wind energy in electricity consumption is growing. The introduction of signicant amounts of wind energy into power systems makes accurate wind forecasting a crucial element of modern electrical...... grids. These systems require forecasts with temporal scales of tens of minutes to a few days in advance at wind farm locations. Traditionally these forecasts predict the wind at turbine hub heights; this information is then converted by transmission system operators and energy companies into predictions...... of power output at wind farms. Since the power available in the wind is proportional to the wind speed cubed, even small wind forecast errors result in large power prediction errors. Accurate wind forecasts are worth billions of dollars annually; forecast improvements will result in reduced costs...
DEFF Research Database (Denmark)
Raja, Muhammad Imran; Hussain, Dil muhammed Akbar; Soltani, Mohsen
2017-01-01
Multivariable disturbance accommodated observer based control (DOBC) scheme is presented to mitigate loads generated due to wind shear and tower shadow using individual blade pitch for above-rated wind speed condition of wind turbine. Wind shear and tower shadow add flickers as 1p, 3p, 6p and so on......, (p is the rotor rotational frequency) for three-bladed wind turbine. Novel DOBC with individual pitch control (IPC) to mitigate the flickers is presented and linear state-space model of wind turbine with tower dynamics is developed. The proposed controller is tuned using optimal control theory...... density of generator speed, drive-train torsion and tower fore-aft moment shows better mitigation to the flickers by proposed controller as compared with proportional–integral (PI) and disturbance accommodation control (DAC) with collective pitch control. Furthermore, it shows less degradation...
Model predictive control for wind power gradients
DEFF Research Database (Denmark)
Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp
2015-01-01
We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....
Robust Predictive Functional Control for Flight Vehicles Based on Nonlinear Disturbance Observer
Directory of Open Access Journals (Sweden)
Yinhui Zhang
2015-01-01
Full Text Available A novel robust predictive functional control based on nonlinear disturbance observer is investigated in order to address the control system design for flight vehicles with significant uncertainties, external disturbances, and measurement noise. Firstly, the nonlinear longitudinal dynamics of the flight vehicle are transformed into linear-like state-space equations with state-dependent coefficient matrices. And then the lumped disturbances are considered in the linear structure predictive model of the predictive functional control to increase the precision of the predictive output and resolve the intractable mismatched disturbance problem. As the lumped disturbances cannot be derived or measured directly, the nonlinear disturbance observer is applied to estimate the lumped disturbances, which are then introduced to the predictive functional control to replace the unknown actual lumped disturbances. Consequently, the robust predictive functional control for the flight vehicle is proposed. Compared with the existing designs, the effectiveness and robustness of the proposed flight control are illustrated and validated in various simulation conditions.
Advanced modelling of doubly fed induction generator wind turbine under network disturbance
DEFF Research Database (Denmark)
Seman, S.; Iov, Florin; Niiranen, J.
This paper presents a variable speed wind turbine simulator. The simulator is used for a 2 MW wind turbine transient behavior study during a short-term symmetrical network disturbance. The mechanical part of wind turbine model consists of the rotor aerodynamic model, the wind turbine control...... converter, the model of the main transformer and a simple model of the grid. The simulation results obtained by means of the detailed wind turbine model are compared with the results obtained from a simplified simulator with an analytical model and FEM model of DFIG. The comparison of the results shows...... and the drive train model. The Doubly Fed Induction Generator (DFIG) is represented by an analytical two-axis model with constant lumped parameters and by Finite Element Method (FEM) based model. The model of the DFIG is coupled with the model of the passive crowbar protected and DTC controlled frequency...
Wind farms production: Control and prediction
El-Fouly, Tarek Hussein Mostafa
Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect
Wind Predictions Upstream Wind Turbines from a LiDAR Database
Directory of Open Access Journals (Sweden)
Soledad Le Clainche
2018-03-01
Full Text Available This article presents a new method to predict the wind velocity upstream a horizontal axis wind turbine from a set of light detection and ranging (LiDAR measurements. The method uses higher order dynamic mode decomposition (HODMD to construct a reduced order model (ROM that can be extrapolated in space. LiDAR measurements have been carried out upstream a wind turbine at six different planes perpendicular to the wind turbine axis. This new HODMD-based ROM predicts with high accuracy the wind velocity during a timespan of 24 h in a plane of measurements that is more than 225 m far away from the wind turbine. Moreover, the technique introduced is general and obtained with an almost negligible computational cost. This fact makes it possible to extend its application to both vertical axis wind turbines and real-time operation.
Basic disturbances of information processing in psychosis prediction.
Bodatsch, Mitja; Klosterkötter, Joachim; Müller, Ralf; Ruhrmann, Stephan
2013-01-01
The basic symptoms (BS) approach provides a valid instrument in predicting psychosis onset and represents moreover a significant heuristic framework for research. The term "basic symptoms" denotes subtle changes of cognition and perception in the earliest and prodromal stages of psychosis development. BS are thought to correspond to disturbances of neural information processing. Following the heuristic implications of the BS approach, the present paper aims at exploring disturbances of information processing, revealed by functional magnetic resonance imaging (fMRI) and electro-encephalographic as characteristics of the at-risk state of psychosis. Furthermore, since high-risk studies employing ultra-high-risk criteria revealed non-conversion rates commonly exceeding 50%, thus warranting approaches that increase specificity, the potential contribution of neural information processing disturbances to psychosis prediction is reviewed. In summary, the at-risk state seems to be associated with information processing disturbances. Moreover, fMRI investigations suggested that disturbances of language processing domains might be a characteristic of the prodromal state. Neurophysiological studies revealed that disturbances of sensory processing may assist psychosis prediction in allowing for a quantification of risk in terms of magnitude and time. The latter finding represents a significant advancement since an estimation of the time to event has not yet been achieved by clinical approaches. Some evidence suggests a close relationship between self-experienced BS and neural information processing. With regard to future research, the relationship between neural information processing disturbances and different clinical risk concepts warrants further investigations. Thereby, a possible time sequence in the prodromal phase might be of particular interest.
A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System
Directory of Open Access Journals (Sweden)
Xiaoliang Yang
2017-07-01
Full Text Available A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS. The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances and to satisfy the stator power response of the system. Within the proposed control method, the control scheme for the rotor side converter (RSC is developed on the model predictive control. Firstly, the self-adaptive reference trajectory is established from the deduced discrete state-space equation of the generator. Then, the rotor voltage is calculated by minimizing the global performance index under the current prediction steps at the sampling instant. Through the control scheme for the grid side converter (GSC and wind turbine, we have re-applied the conventional control. The effectiveness of the proposed control strategy is verified via time domain simulation of a 150 kW-575 V DFIG-WECS using Matlab/Simulink. The simulation result shows that the control of the DFIG with the proposed control method can enhance the steady and dynamic response capability better than the conventional ones when the system faces errors due to the parameter perturbations, external disturbances and the rotor speed.
Robust Helicopter Stabilization in the Face of Wind Disturbance
DEFF Research Database (Denmark)
A. Danapalasingam, Kumeresan; Leth, John-Josef; la Cour-Harbo, Anders
2010-01-01
When a helicopter is required to hover with minimum deviations from a desired position without measurements of an affecting persistent wind disturbance, a robustly stabilizing control action is vital. In this paper, the stabilization of the position and translational velocity of a nonlinear...... controller is then designed based on nonlinear adaptive output regulations and robust stabilization of a chain of integrators by a saturated feedback. Simulation results show the effectiveness of the control design in the stabilization of helicopter motion and the built-in robustness of the controller...
Composite control for raymond mill based on model predictive control and disturbance observer
Directory of Open Access Journals (Sweden)
Dan Niu
2016-03-01
Full Text Available In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.
Ensemble modeling to predict habitat suitability for a large-scale disturbance specialist
Quresh S. Latif; Victoria A. Saab; Jonathan G. Dudley; Jeff P. Hollenbeck
2013-01-01
To conserve habitat for disturbance specialist species, ecologists must identify where individuals will likely settle in newly disturbed areas. Habitat suitability models can predict which sites at new disturbances will most likely attract specialists. Without validation data from newly disturbed areas, however, the best approach for maximizing predictive accuracy can...
Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances
Sarda, Edoardo I.; Qu, Huajin; Bertaska, Ivan R.; von Ellenrieder, Karl D.
2017-01-01
Field trials of a 4 meter long, 180 kilogram, unmanned surface vehicle (USV) have been conducted to evaluate the performance of station-keeping heading and position controllers in an outdoor marine environment disturbed by wind and current. The USV has a twin hull configuration and a custom-designed propulsion system, which consists of two azimuthing thrusters, one for each hull. Nonlinear proportional derivative, backstepping and sliding mode feedback controllers were tested in winds of abou...
Improved Wind Speed Prediction Using Empirical Mode Decomposition
Directory of Open Access Journals (Sweden)
ZHANG, Y.
2018-05-01
Full Text Available Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD, the Radial Basis Function Neural Network (RBF and the Least Square Support Vector Machine (SVM, an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM, the EMD-RBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power.
Short-term wind power prediction
DEFF Research Database (Denmark)
Joensen, Alfred K.
2003-01-01
, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity...
Skill forecasting from ensemble predictions of wind power
DEFF Research Database (Denmark)
Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik
2009-01-01
Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...
Wind prediction in Malaysia using Mycielski-1 approach
Lee, S. W.; Kok, B. C.; Goh, K. C.; Goh, H. H.
2012-11-01
In this paper, the wind speed prediction in Kudat, Malaysia had been done by using Mycielski-1 approach. There is some improvement in obtaining the random number of Mycielski-1. The wind prediction is important to study a favorable site's wind potential. The prediction is based on 3 years history data provided by Meteorology Department of Malaysia and 1 year data as the reference to check the accuracy of this algorithm. The basic concept of this algorithm is to predict the next value by looking to history data. The result shows the prediction of Mycielski-1 algorithm is promising. The wind speed is predicted in order to obtain the mean power for energy planning.
Bayesian Predictive Models for Rayleigh Wind Speed
DEFF Research Database (Denmark)
Shahirinia, Amir; Hajizadeh, Amin; Yu, David C
2017-01-01
predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....
Li, Shengquan; Zhang, Kezhao; Li, Juan; Liu, Chao
2016-03-01
This paper deals with the critical issue in a wind energy conversion system (WECS) based on a direct-driven permanent magnet synchronous generator (PMSG): the rejection of lumped disturbance, including the system uncertainties in the internal dynamics and unknown external forces. To simultaneously track the motor speed in real time and capture the maximum power, a maximum power point tracking strategy is proposed based on active disturbance rejection control (ADRC) theory. In real application, system inertia, drive torque and some other parameters change in a wide range with the variations of disturbances and wind speeds, which substantially degrade the performance of WECS. The ADRC design must incorporate the available model information into an extended state observer (ESO) to compensate the lumped disturbance efficiently. Based on this principle, a model-compensation ADRC is proposed in this paper. Simulation study is conducted to evaluate the performance of the proposed control strategy. It is shown that the effect of lumped disturbance is compensated in a more effective way compared with the traditional ADRC approach. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Bacles, Cecile F E
2014-01-01
Understanding the consequences of habitat disturbance on mating patterns although pollen and seed dispersal in forest trees has been a long-standing theme of forest and conservation genetics. Forest ecosystems face global environmental pressures from timber exploitation to genetic pollution and climate change, and it is therefore essential to comprehend how disturbances may alter the dispersal of genes and their establishment in tree populations in order to formulate relevant recommendations for sustainable resource management practices and realistic predictions of potential adaptation to climate change by means of range shift or expansion (Kremer et al. 2012). However, obtaining reliable evidence of disturbance-induced effects on gene dispersal processes from empirical evaluation of forest tree populations is difficult. Indeed, tree species share characteristics such as high longevity, long generation time and large reproductive population size, which may impede the experimenter's ability to assess parameters at the spatial and time scales at which any change may occur (Petit and Hampe 2006). It has been suggested that appropriate study designs should encompass comparison of populations before and after disturbance as well as account for demonstrated variation in conspecific density, that is, the spatial distribution of mates, and forest density, including all species and relating to alteration in landscape openness (Bacles & Jump 2011). However, more often than not, empirical studies aiming to assess the consequences of habitat disturbance on genetic processes in tree populations assume rather than quantify a change in tree densities in forests under disturbance and generally fail to account for population history, which may lead to inappropriate interpretation of a causal relationship between population genetic structure and habitat disturbance due to effects of unmonitored confounding variables (Gauzere et al. 2013). In this issue, Shohami and Nathan (2014
DEFF Research Database (Denmark)
Tan, Jin; Hu, Weihao; Wang, Xiaoru
2015-01-01
The main focus of forced low frequency oscillations is to analyze the disturbance source and the origin of forced oscillations. In this paper, the origin of low-frequency periodical oscillations induced by wind turbines’ mechanical power is investigated and the mechanism is studied of fluctuating...... power transfer through permanent magnet generator wind turbine system. Considering the tower shadow and the wind shear effect, the mechanical and generator coupling model is developed by PSCAD. Simulation is done to analyze the impacts on output power of operation points and mechanical fluctuation...... components. It is shown that when the oscillation frequency of tower shadow coincides with the system natural frequency, it may cause forced oscillations, whereas, the wind shear and natural wind speed fluctuation are not likely to induce forced oscillations....
Frequency weighted model predictive control of wind turbine
DEFF Research Database (Denmark)
Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood
2013-01-01
This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...
Directory of Open Access Journals (Sweden)
P. Wintoft
2005-11-01
Full Text Available The 7-10 November 2004 period contains two events for which the local ground magnetic field was severely disturbed and simultaneously, the solar wind displayed several shocks and negative Bz periods. Using empirical models the 10-min RMS and at Brorfelde (BFE, 11.67° E, 55.63° N, Denmark, are predicted. The models are recurrent neural networks with 10-min solar wind plasma and magnetic field data as inputs. The predictions show a good agreement during 7 November, up until around noon on 8 November, after which the predictions become significantly poorer. The correlations between observed and predicted log RMS is 0.77 during 7-8 November but drops to 0.38 during 9-10 November. For RMS the correlations for the two periods are 0.71 and 0.41, respectively. Studying the solar wind data for other L1-spacecraft (WIND and SOHO it seems that the ACE data have a better agreement to the near-Earth solar wind during the first two days as compared to the last two days. Thus, the accuracy of the predictions depends on the location of the spacecraft and the solar wind flow direction. Another finding, for the events studied here, is that the and models showed a very different dependence on Bz. The model is almost independent of the solar wind magnetic field Bz, except at times when Bz is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on Bz at all times.
Kishore Kumar, G.; Nesse Tyssøy, H.; Williams, Bifford P.
2018-03-01
We investigate the possibility that sufficiently large electric fields and/or ionization during geomagnetic disturbed conditions may invalidate the assumptions applied in the retrieval of neutral horizontal winds from meteor and/or lidar measurements. As per our knowledge, the possible errors in the wind estimation have never been reported. In the present case study, we have been using co-located meteor radar and sodium resonance lidar zonal wind measurements over Andenes (69.27°N, 16.04°E) during intense substorms in the declining phase of the January 2005 solar proton event (21-22 January 2005). In total, 14 h of measurements are available for the comparison, which covers both quiet and disturbed conditions. For comparison, the lidar zonal wind measurements are averaged over the same time and altitude as the meteor radar wind measurements. High cross correlations (∼0.8) are found in all height regions. The discrepancies can be explained in light of differences in the observational volumes of the two instruments. Further, we extended the comparison to address the electric field and/or ionization impact on the neutral wind estimation. For the periods of low ionization, the neutral winds estimated with both instruments are quite consistent with each other. During periods of elevated ionization, comparatively large differences are noticed at the highermost altitude, which might be due to the electric field and/or ionization impact on the wind estimation. At present, one event is not sufficient to make any firm conclusion. Further study with more co-located measurements are needed to test the statistical significance of the result.
Short-Term Wind Speed Prediction Using EEMD-LSSVM Model
Directory of Open Access Journals (Sweden)
Aiqing Kang
2017-01-01
Full Text Available Hybrid Ensemble Empirical Mode Decomposition (EEMD and Least Square Support Vector Machine (LSSVM is proposed to improve short-term wind speed forecasting precision. The EEMD is firstly utilized to decompose the original wind speed time series into a set of subseries. Then the LSSVM models are established to forecast these subseries. Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries. Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction. The performance of hybrid model is evaluated based on six metrics. Compared with LSSVM, Back Propagation Neural Networks (BP, Auto-Regressive Integrated Moving Average (ARIMA, combination of Empirical Mode Decomposition (EMD with LSSVM, and hybrid EEMD with ARIMA models, the wind speed forecasting results show that the proposed hybrid model outperforms these models in terms of six metrics. Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.
The wind power prediction research based on mind evolutionary algorithm
Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina
2018-04-01
When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.
Using meteorological forecasts in on-line predictions of wind power
DEFF Research Database (Denmark)
Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik
1999-01-01
This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...
Adaptive Disturbance Estimation for Offset-Free SISO Model Predictive Control
DEFF Research Database (Denmark)
Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay
2011-01-01
Offset free tracking in Model Predictive Control requires estimation of unmeasured disturbances or the inclusion of an integrator. An algorithm for estimation of an unknown disturbance based on adaptive estimation with time varying forgetting is introduced and benchmarked against the classical...
Assessment and prediction of wind turbine noise
International Nuclear Information System (INIS)
Lowson, M.V.
1993-01-01
The significance of basic aerodynamic noise sources for wind turbine noise are assessed, using information on the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. Based on this analysis, a new model for prediction of wind turbine noise is presented and comparisons made between prediction and experiment. The model is based on well established aeroacoustic theory and published laboratory data for the two principal sources, inflow turbulence and boundary layer trailing edge interaction. The new method gives good agreement with experiment with the case studied so far. Parametric trends and sensitivities for the model are presented. Comparisons with previous prediction methods are also given. A consequence of the new model is to put more emphasis on boundary layer trailing edge interaction as a noise source. There are prospects for reducing noise from this source detail changes to the wind turbine design. (author)
Short-term wind power prediction based on LSSVM–GSA model
International Nuclear Information System (INIS)
Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong
2015-01-01
Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction
Stephen D White; Justin L. Hart; Callie J. Schweitzer; Daniel C. Dey
2015-01-01
Natural disturbances play important roles in shaping the structure and composition of all forest ecosystems and can be used to inform silvicultural practices. Canopy disturbances are often classified along a gradient ranging from highly localized, gap-scale events to stand-replacing events. Wind storms such as downbursts, derechos, and low intensity tornadoes typically...
Application of the WEPS and SWEEP models to non-agricultural disturbed lands
Directory of Open Access Journals (Sweden)
J. Tatarko
2016-12-01
Full Text Available Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10 has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP, has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but
Application of the WEPS and SWEEP models to non-agricultural disturbed lands.
Tatarko, J; van Donk, S J; Ascough, J C; Walker, D G
2016-12-01
Wind erosion not only affects agricultural productivity but also soil, air, and water quality. Dust and specifically particulate matter ≤10 μm (PM-10) has adverse effects on respiratory health and also reduces visibility along roadways, resulting in auto accidents. The Wind Erosion Prediction System (WEPS) was developed by the USDA-Agricultural Research Service to simulate wind erosion and provide for conservation planning on cultivated agricultural lands. A companion product, known as the Single-Event Wind Erosion Evaluation Program (SWEEP), has also been developed which consists of the stand-alone WEPS erosion submodel combined with a graphical interface to simulate soil loss from single (i.e., daily) wind storm events. In addition to agricultural lands, wind driven dust emissions also occur from other anthropogenic sources such as construction sites, mined and reclaimed areas, landfills, and other disturbed lands. Although developed for agricultural fields, WEPS and SWEEP are useful tools for simulating erosion by wind for non-agricultural lands where typical agricultural practices are not employed. On disturbed lands, WEPS can be applied for simulating long-term (i.e., multi-year) erosion control strategies. SWEEP on the other hand was developed specifically for disturbed lands and can simulate potential soil loss for site- and date-specific planned surface conditions and control practices. This paper presents novel applications of WEPS and SWEEP for developing erosion control strategies on non-agricultural disturbed lands. Erosion control planning with WEPS and SWEEP using water and other dust suppressants, wind barriers, straw mulch, re-vegetation, and other management practices is demonstrated herein through the use of comparative simulation scenarios. The scenarios confirm the efficacy of the WEPS and SWEEP models as valuable tools for supporting the design of erosion control plans for disturbed lands that are not only cost-effective but also incorporate
Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.
de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E
2012-01-01
Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.
Jia, R. L.; Li, X. R.; Liu, L. C.; Gao, Y. H.
2012-04-01
Sand burial and wind are two predominant natural disturbances in the desert ecosystems worldwide. However, the effects of sand burial and wind disturbances on moss soil crusts are still largely unexplored. In this study, two sets of experiments were conducted separately to evaluated the effects of sand burial (sand depth of 0, 1, 2, 3 and 4 mm) and wind blowing (wind speed of 0.2, 3, 6 and 9ms-1) on ecophysiological variables of two moss soil crusts collected from a revegetated area of the Tengger Desert, Northern China. Firstly, the results from the sand burial experiment revealed that respiration rate was significantly decreased and that moss shoot elongation was significantly increased after burial. In addition, Bryum argenteum crust showed the fastest speed of emergence and highest tolerance index, followed by Didymodon vinealis crust. This sequence was consistent with the successional order of the two moss crusts that happened in our study area, indicating that differential sand burial tolerance explains their succession sequence. Secondly, the results from the wind experiment showed that CO2 exchange, PSII photochemical efficiency, photosynthetic pigments, shoot upgrowth, productivity and regeneration potential of the two moss soil crust mentioned above were all substantially depressed. Furthermore, D. vinealis crust exhibited stronger wind resistance than B. argenteum crust from all aspects mentioned above. And this is comparison was identical with their contrasting microhabitats with B. argenteum crust being excluded from higher wind speed microsites in the windward slopes, suggesting that the differential wind resistance of moss soil crusts explains their microdistribution pattern. In conclusion, the ecogeomorphological processes of moss soil crusts in desert ecosystems can be largely determined by natural disturbances caused by sand burial and wind blowing in desert ecosystems.
Model Predictive Control with Constraints of a Wind Turbine
DEFF Research Database (Denmark)
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
2007-01-01
Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure a...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers.......Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...
Wind speed prediction using statistical regression and neural network
Indian Academy of Sciences (India)
Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve fitting,Auto Regressive ...
Effect of accuracy of wind power prediction on power system operator
Schlueter, R. A.; Sigari, G.; Costi, T.
1985-01-01
This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.
Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand
2014-01-01
In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.
Directory of Open Access Journals (Sweden)
Manuela de Lucas
Full Text Available BACKGROUND: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. METHODOLOGY/PRINCIPAL FINDINGS: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. CONCLUSIONS: Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed. We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.
Energy Technology Data Exchange (ETDEWEB)
Kamp, Derek van der [University of Victoria, Pacific Climate Impacts Consortium, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Curry, Charles L. [Environment Canada University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Monahan, Adam H. [University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada)
2012-04-15
A regression-based downscaling technique was applied to monthly mean surface wind observations from stations throughout western Canada as well as from buoys in the Northeast Pacific Ocean over the period 1979-2006. A predictor set was developed from principal component analysis of the three wind components at 500 hPa and mean sea-level pressure taken from the NCEP Reanalysis II. Building on the results of a companion paper, Curry et al. (Clim Dyn 2011), the downscaling was applied to both wind speed and wind components, in an effort to evaluate the utility of each type of predictand. Cross-validated prediction skill varied strongly with season, with autumn and summer displaying the highest and lowest skill, respectively. In most cases wind components were predicted with better skill than wind speeds. The predictive ability of wind components was found to be strongly related to their orientation. Wind components with the best predictions were often oriented along topographically significant features such as constricted valleys, mountain ranges or ocean channels. This influence of directionality on predictive ability is most prominent during autumn and winter at inland sites with complex topography. Stations in regions with relatively flat terrain (where topographic steering is minimal) exhibit inter-station consistencies including region-wide seasonal shifts in the direction of the best predicted wind component. The conclusion that wind components can be skillfully predicted only over a limited range of directions at most stations limits the scope of statistically downscaled wind speed predictions. It seems likely that such limitations apply to other regions of complex terrain as well. (orig.)
Control design methods for floating wind turbines for optimal disturbance rejection
Lemmer, Frank; Schlipf, David; Cheng, Po Wen
2016-09-01
An analysis of the floating wind turbine as a multi-input-multi-output system investigating the effect of the control inputs on the system outputs is shown. These effects are compared to the ones of the disturbances from wind and waves in order to give insights for the selection of the control layout. The frequencies with the largest impact on the outputs due to limited effect of the controlled variables are identified. Finally, an optimal controller is designed as a benchmark and compared to a conventional PI-controller using only the rotor speed as input. Here, the previously found system properties, especially the difficulties to damp responses to wave excitation, are confirmed and verified through a spectral analysis with realistic environmental conditions. This comparison also assesses the quality of the employed simplified linear simulation model compared to the nonlinear model and shows that such an efficient frequency-domain evaluation for control design is feasible.
Design and Application of Offset-Free Model Predictive Control Disturbance Observation Method
Directory of Open Access Journals (Sweden)
Xue Wang
2016-01-01
Full Text Available Model predictive control (MPC with its lower request to the mathematical model, excellent control performance, and convenience online calculation has developed into a very important subdiscipline with rich theory foundation and practical application. However, unmeasurable disturbance is widespread in industrial processes, which is difficult to deal with directly at present. In most of the implemented MPC strategies, the method of incorporating a constant output disturbance into the process model is introduced to solve this problem, but it fails to achieve offset-free control once the unmeasured disturbances access the process. Based on the Kalman filter theory, the problem is solved by using a more general disturbance model which is superior to the constant output disturbance model. This paper presents the necessary conditions for offset-free model predictive control based on the model. By applying disturbance model, the unmeasurable disturbance vectors are augmented as the states of control system, and the Kalman filer is used to estimate unmeasurable disturbance and its effect on the output. Then, the dynamic matrix control (DMC algorithm is improved by utilizing the feed-forward compensation control strategy with the disturbance estimated.
Neural Network Classifiers for Local Wind Prediction.
Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz
2004-05-01
This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.
Model output statistics applied to wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Joensen, A; Giebel, G; Landberg, L [Risoe National Lab., Roskilde (Denmark); Madsen, H; Nielsen, H A [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
Directory of Open Access Journals (Sweden)
P. Wintoft
2005-11-01
Full Text Available The 7-10 November 2004 period contains two events for which the local ground magnetic field was severely disturbed and simultaneously, the solar wind displayed several shocks and negative Bz periods. Using empirical models the 10-min RMS and at Brorfelde (BFE, 11.67° E, 55.63° N, Denmark, are predicted. The models are recurrent neural networks with 10-min solar wind plasma and magnetic field data as inputs. The predictions show a good agreement during 7 November, up until around noon on 8 November, after which the predictions become significantly poorer. The correlations between observed and predicted log RMS is 0.77 during 7-8 November but drops to 0.38 during 9-10 November. For RMS the correlations for the two periods are 0.71 and 0.41, respectively. Studying the solar wind data for other L1-spacecraft (WIND and SOHO it seems that the ACE data have a better agreement to the near-Earth solar wind during the first two days as compared to the last two days. Thus, the accuracy of the predictions depends on the location of the spacecraft and the solar wind flow direction. Another finding, for the events studied here, is that the and models showed a very different dependence on Bz. The model is almost independent of the solar wind magnetic field Bz, except at times when Bz is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on Bz at all times.
A model to predict the power output from wind farms
Energy Technology Data Exchange (ETDEWEB)
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.
Tracking heliospheric disturbances by interplanetary scintillation
Directory of Open Access Journals (Sweden)
M. Tokumaru
2006-01-01
Full Text Available Coronal mass ejections are known as a solar cause of significant geospace disturbances, and a fuller elucidation of their physical properties and propagation dynamics is needed for space weather predictions. The scintillation of cosmic radio sources caused by turbulence in the solar wind (interplanetary scintillation; IPS serves as an effective ground-based method for monitoring disturbances in the heliosphere. We studied global properties of transient solar wind streams driven by CMEs using 327-MHz IPS observations of the Solar-Terrestrial Environment Laboratory (STEL of Nagoya University. In this study, we reconstructed three-dimensional features of the interplanetary (IP counterpart of the CME from the IPS data by applying the model fitting technique. As a result, loop-shaped density enhancements were deduced for some CME events, whereas shell-shaped high-density regions were observed for the other events. In addition, CME speeds were found to evolve significantly during the propagation between the corona and 1 AU.
Skill forecasting from different wind power ensemble prediction methods
International Nuclear Information System (INIS)
Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George
2007-01-01
This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed
Influence of disturbance on temperate forest productivity
Peters, Emily B.; Wythers, Kirk R.; Bradford, John B.; Reich, Peter B.
2013-01-01
Climate, tree species traits, and soil fertility are key controls on forest productivity. However, in most forest ecosystems, natural and human disturbances, such as wind throw, fire, and harvest, can also exert important and lasting direct and indirect influence over productivity. We used an ecosystem model, PnET-CN, to examine how disturbance type, intensity, and frequency influence net primary production (NPP) across a range of forest types from Minnesota and Wisconsin, USA. We assessed the importance of past disturbances on NPP, net N mineralization, foliar N, and leaf area index at 107 forest stands of differing types (aspen, jack pine, northern hardwood, black spruce) and disturbance history (fire, harvest) by comparing model simulations with observations. The model reasonably predicted differences among forest types in productivity, foliar N, leaf area index, and net N mineralization. Model simulations that included past disturbances minimally improved predictions compared to simulations without disturbance, suggesting the legacy of past disturbances played a minor role in influencing current forest productivity rates. Modeled NPP was more sensitive to the intensity of soil removal during a disturbance than the fraction of stand mortality or wood removal. Increasing crown fire frequency resulted in lower NPP, particularly for conifer forest types with longer leaf life spans and longer recovery times. These findings suggest that, over long time periods, moderate frequency disturbances are a relatively less important control on productivity than climate, soil, and species traits.
Directory of Open Access Journals (Sweden)
Yun-Tao Shi
2018-01-01
Full Text Available Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs, how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC fault-tolerant controller with the Conditional Value at Risk (CVaR objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.
Using machine learning to predict wind turbine power output
International Nuclear Information System (INIS)
Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P
2013-01-01
Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site. (letter)
Directory of Open Access Journals (Sweden)
S. Oyama
2008-06-01
Full Text Available Lower-thermospheric winds at high latitudes during moderately-disturbed geomagnetic conditions were studied using data obtained with the European Incoherent Scatter (EISCAT Kiruna-Sodankylä-Tromsø (KST ultrahigh frequency (UHF radar system on 9–10 September 2004. The antenna-beam configuration was newly designed to minimize the estimated measurement error of the vertical neutral-wind speed in the lower thermosphere. This method was also available to estimate the meridional and zonal components. The vertical neutral-wind speed at 109 km, 114 km, and 120 km heights showed large upward motions in excess of 30 m s−1 in association with an ionospheric heating event. Large downward speeds in excess of −30 m s−1 were also observed before and after the heating event. The meridional neutral-wind speed suddenly changed its direction from equatorward to poleward when the heating event began, and then returned equatorward coinciding with a decrease in the heating event. The magnetometer data from northern Scandinavia suggested that the center of the heated region was located about 80 km equatorward of Tromsø. The pressure gradient caused the lower-thermospheric wind to accelerate obliquely upward over Tromsø in the poleward direction. Acceleration of the neutral wind flowing on a vertically tilted isobar produced vertical wind speeds larger by more than two orders of magnitude than previously predicted, but still an order of magnitude smaller than observed speeds.
Directory of Open Access Journals (Sweden)
S. Oyama
2008-06-01
Full Text Available Lower-thermospheric winds at high latitudes during moderately-disturbed geomagnetic conditions were studied using data obtained with the European Incoherent Scatter (EISCAT Kiruna-Sodankylä-Tromsø (KST ultrahigh frequency (UHF radar system on 9–10 September 2004. The antenna-beam configuration was newly designed to minimize the estimated measurement error of the vertical neutral-wind speed in the lower thermosphere. This method was also available to estimate the meridional and zonal components. The vertical neutral-wind speed at 109 km, 114 km, and 120 km heights showed large upward motions in excess of 30 m s−1 in association with an ionospheric heating event. Large downward speeds in excess of −30 m s−1 were also observed before and after the heating event. The meridional neutral-wind speed suddenly changed its direction from equatorward to poleward when the heating event began, and then returned equatorward coinciding with a decrease in the heating event. The magnetometer data from northern Scandinavia suggested that the center of the heated region was located about 80 km equatorward of Tromsø. The pressure gradient caused the lower-thermospheric wind to accelerate obliquely upward over Tromsø in the poleward direction. Acceleration of the neutral wind flowing on a vertically tilted isobar produced vertical wind speeds larger by more than two orders of magnitude than previously predicted, but still an order of magnitude smaller than observed speeds.
Predicting the impacts of anthropogenic disturbances on marine populations
DEFF Research Database (Denmark)
Nabe-Nielsen, Jacob; van Beest, Floris; Grimm, Volker
Marine ecosystems are increasingly exposed to anthropogenic disturbances that cause animals to change behavior and move away from potential foraging grounds. Here we present a process-based modeling framework for assessing population consequences of such sub-lethal behavioral effects. It builds...... on how disturbances influence animal movements, and how this in turn affect their foraging and energetics. The animals’ tendency to move away from disturbances is directly related to the experienced noise level. The reduced foraging in noisy areas affects the animals’ energy budget, fitness...... that determine animal fitness, are expected to have high predictive power in novel environments, making them ideal tools for marine management....
Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances
Juang, Jer-Nan; Eure, Kenneth W.
1998-01-01
Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.
Liao, Qianjiahua; Huang, Zheng; Li, Shu; Wang, Yi; Liu, Yuqing; Luo, Ran; Shang, Jingge
2018-05-28
Wind-wave disturbances frequently disperse sediment particles into overlying water, which facilitates the adsorption and desorption of contaminants in aquatic ecosystems. Tetracycline (TC) and sulfadimidine (SM2) are common antibiotics that are frequently found in aquatic environments. This study utilized microcosms, comprising sediment and water from Lake Taihu, China, to examine the adsorption and desorption of TC and SM2 under different wind-wave disturbances in a shallow lake environment. The adsorption experiments were conducted with three different concentrations (1, 5, 10 mg/L) of TC and SM2 in the overlying water, and two different (background and strong) wind-wave conditions for 72 h. Subsequently, four microcosms were employed in a 12-h desorption study. Analysis of adsorption progress showed that TC concentration in the overlying water decreased quickly, while SM2 remained almost constant. In the desorption experiments, SM2 released to the overlying water was an order of magnitude greater than TC. These results indicate that sediment particles strongly adsorb TC but weakly adsorb SM2. Compared to background conditions, the strong wind-wave conditions resulted in higher concentrations of TC and SM2 in sediment and facilitated their migration to deeper sediment during adsorption, correspondingly promoting greater release of TC and SM2 from sediment particles into the overlying water during desorption.
Improving urban wind flow predictions through data assimilation
Sousa, Jorge; Gorle, Catherine
2017-11-01
Computational fluid dynamic is fundamentally important to several aspects in the design of sustainable and resilient urban environments. The prediction of the flow pattern for example can help to determine pedestrian wind comfort, air quality, optimal building ventilation strategies, and wind loading on buildings. However, the significant variability and uncertainty in the boundary conditions poses a challenge when interpreting results as a basis for design decisions. To improve our understanding of the uncertainties in the models and develop better predictive tools, we started a pilot field measurement campaign on Stanford University's campus combined with a detailed numerical prediction of the wind flow. The experimental data is being used to investigate the potential use of data assimilation and inverse techniques to better characterize the uncertainty in the results and improve the confidence in current wind flow predictions. We consider the incoming wind direction and magnitude as unknown parameters and perform a set of Reynolds-averaged Navier-Stokes simulations to build a polynomial chaos expansion response surface at each sensor location. We subsequently use an inverse ensemble Kalman filter to retrieve an estimate for the probabilistic density function of the inflow parameters. Once these distributions are obtained, the forward analysis is repeated to obtain predictions for the flow field in the entire urban canopy and the results are compared with the experimental data. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR.
International Nuclear Information System (INIS)
Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.
2004-01-01
One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)
Ultra-Short-Term Wind Power Prediction Using a Hybrid Model
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.
Probabilistic maximum-value wind prediction for offshore environments
DEFF Research Database (Denmark)
Staid, Andrea; Pinson, Pierre; Guikema, Seth D.
2015-01-01
statistical models to predict the full distribution of the maximum-value wind speeds in a 3 h interval. We take a detailed look at the performance of linear models, generalized additive models and multivariate adaptive regression splines models using meteorological covariates such as gust speed, wind speed......, convective available potential energy, Charnock, mean sea-level pressure and temperature, as given by the European Center for Medium-Range Weather Forecasts forecasts. The models are trained to predict the mean value of maximum wind speed, and the residuals from training the models are used to develop...... the full probabilistic distribution of maximum wind speed. Knowledge of the maximum wind speed for an offshore location within a given period can inform decision-making regarding turbine operations, planned maintenance operations and power grid scheduling in order to improve safety and reliability...
Prediction of boundary-layer transition caused by crossflow disturbances
Nomura, Toshiyuki; 野村 聡幸
1999-01-01
A prediction system for boundary layer transition is developed which consists of the Navier-Stokes code computing a compressible boundary layer, the linear PSE (Parabolized Stability Equations) code computing the spatial growth of a disturbance, and the N-factor code integrating the growth rate. The system is applied to the case that the transition of the compressible boundary layer on a swept cylinder is caused by cross flow disturbances which have the same spanwise wavelength as observed in...
Wind Power Plant Prediction by Using Neural Networks: Preprint
Energy Technology Data Exchange (ETDEWEB)
Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.
2012-08-01
This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.
The state of the art of predicting noise-induced sleep disturbance in field settings.
Fidell, Sanford; Tabachnick, Barbara; Pearsons, Karl S
2010-01-01
Several relationships between intruding noises (largely aircraft) and sleep disturbance have been inferred from the findings of a handful of field studies. Comparisons of sleep disturbance rates predicted by the various relationships are complicated by inconsistent data collection methods and definitions of predictor variables and predicted quantities. None of the relationships is grounded in theory-based understanding, and some depend on questionable statistical assumptions and analysis procedures. The credibility, generalizability, and utility of sleep disturbance predictions are also limited by small and nonrepresentative samples of test participants, and by restricted (airport-specific and relatively short duration) circumstances of exposure. Although expedient relationships may be the best available, their predictions are of only limited utility for policy analysis and regulatory purposes, because they account for very little variance in the association between environmental noise and sleep disturbance, have characteristically shallow slopes, have not been well validated in field settings, are highly context-dependent, and do not squarely address the roles and relative importance of nonacoustic factors in sleep disturbance. Such relationships offer the appearance more than the substance of precision and objectivity. Truly useful, population-level prediction and genuine understanding of noise-induced sleep disturbance will remain beyond reach for the foreseeable future, until the findings of field studies of broader scope and more sophisticated design become available.
The state of the art of predicting noise-induced sleep disturbance in field settings
Directory of Open Access Journals (Sweden)
Sanford Fidell
2010-01-01
Full Text Available Several relationships between intruding noises (largely aircraft and sleep disturbance have been inferred from the findings of a handful of field studies. Comparisons of sleep disturbance rates predicted by the various relationships are complicated by inconsistent data collection methods and definitions of predictor variables and predicted quantities. None of the relationships is grounded in theory-based understanding, and some depend on questionable statistical assumptions and analysis procedures. The credibility, generalizability, and utility of sleep disturbance predictions are also limited by small and nonrepresentative samples of test participants, and by restricted (airport-specific and relatively short duration circumstances of exposure. Although expedient relationships may be the best available, their predictions are of only limited utility for policy analysis and regulatory purposes, because they account for very little variance in the association between environmental noise and sleep disturbance, have characteristically shallow slopes, have not been well validated in field settings, are highly context-dependent, and do not squarely address the roles and relative importance of nonacoustic factors in sleep disturbance. Such relationships offer the appearance more than the substance of precision and objectivity. Truly useful, population-level prediction and genuine understanding of noise-induced sleep disturbance will remain beyond reach for the foreseeable future, until the findings of field studies of broader scope and more sophisticated design become available.
Functional traits help predict post-disturbance demography of tropical trees.
Flores, Olivier; Hérault, Bruno; Delcamp, Matthieu; Garnier, Éric; Gourlet-Fleury, Sylvie
2014-01-01
How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.
International Nuclear Information System (INIS)
Sun, Yanan; Dong, Jizhe; Ding, Lijuan
2017-01-01
Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.
Adjoint Method and Predictive Control for 1-D Flow in NASA Ames 11-Foot Transonic Wind Tunnel
Nguyen, Nhan; Ardema, Mark
2006-01-01
This paper describes a modeling method and a new optimal control approach to investigate a Mach number control problem for the NASA Ames 11-Foot Transonic Wind Tunnel. The flow in the wind tunnel is modeled by the 1-D unsteady Euler equations whose boundary conditions prescribe a controlling action by a compressor. The boundary control inputs to the compressor are in turn controlled by a drive motor system and an inlet guide vane system whose dynamics are modeled by ordinary differential equations. The resulting Euler equations are thus coupled to the ordinary differential equations via the boundary conditions. Optimality conditions are established by an adjoint method and are used to develop a model predictive linear-quadratic optimal control for regulating the Mach number due to a test model disturbance during a continuous pitch
Variable Speed (DFIG) Wind Turbines: Rapid Frequency Response to Power System Disturbances
DEFF Research Database (Denmark)
Chandrashekhara, Divya K; Hansen, Anca Daniela; Sørensen, Poul Ejnar
2009-01-01
This paper examines the effect of integrating large number of wind turbines particularly the double fed induction generator (DFIG) on the virtual inertia of the Danish power system network. The virtual inertia refers to the kinetic energy stored in the rotating masses which can be released...... initially to counter act the frequency change during a power system disturbance. Simulation studies have been carried out on a generic reduced model of a transmission power grid of the Danish TSO Energinet.dk to assess the impact of loss of generation on system frequency. Further, simulation study has been...
Standardizing the performance evaluation of short-term wind prediction models
DEFF Research Database (Denmark)
Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.
2005-01-01
Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....
Directory of Open Access Journals (Sweden)
Xianlei Cheng
2015-01-01
Full Text Available We propose a predictive sliding mode control (PSMC scheme for attitude control of hypersonic vehicle (HV with system uncertainties and external disturbances based on an improved fuzzy disturbance observer (IFDO. First, for a class of uncertain affine nonlinear systems with system uncertainties and external disturbances, we propose a predictive sliding mode control based on fuzzy disturbance observer (FDO-PSMC, which is used to estimate the composite disturbances containing system uncertainties and external disturbances. Afterward, to enhance the composite disturbances rejection performance, an improved FDO-PSMC (IFDO-PSMC is proposed by incorporating a hyperbolic tangent function with FDO to compensate for the approximate error of FDO. Finally, considering the actuator dynamics, the proposed IFDO-PSMC is applied to attitude control system design for HV to track the guidance commands with high precision and strong robustness. Simulation results demonstrate the effectiveness and robustness of the proposed attitude control scheme.
The Storm Time Evolution of the Ionospheric Disturbance Plasma Drifts
Zhang, Ruilong; Liu, Libo; Le, Huijun; Chen, Yiding; Kuai, Jiawei
2017-11-01
In this paper, we use the C/NOFS and ROCSAT-1 satellites observations to analyze the storm time evolution of the disturbance plasma drifts in a 24 h local time scale during three magnetic storms driven by long-lasting southward IMF Bz. The disturbance plasma drifts during the three storms present some common features in the periods dominated by the disturbance dynamo. The newly formed disturbance plasma drifts are upward and westward at night, and downward and eastward during daytime. Further, the disturbance plasma drifts are gradually evolved to present significant local time shifts. The westward disturbance plasma drifts gradually migrate from nightside to dayside. Meanwhile, the dayside downward disturbance plasma drifts become enhanced and shift to later local time. The local time shifts in disturbance plasma drifts are suggested to be mainly attributed to the evolution of the disturbance winds. The strong disturbance winds arisen around midnight can constantly corotate to later local time. At dayside the westward and equatorward disturbance winds can drive the F region dynamo to produce the poleward and westward polarization electric fields (or the westward and downward disturbance drifts). The present results indicate that the disturbance winds corotated to later local time can affect the local time features of the disturbance dynamo electric field.
Using data-driven approach for wind power prediction: A comparative study
International Nuclear Information System (INIS)
Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.
2016-01-01
Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the
Lidar-Enhanced Wind Turbine Control: Past, Present, and Future
Energy Technology Data Exchange (ETDEWEB)
Scholbrock, Andrew; Fleming, Paul; Schlipf, David; Wright, Alan; Johnson, Kathryn; Wang, Na
2016-08-01
The main challenges in harvesting energy from the wind arise from the unknown incoming turbulent wind field. Balancing the competing interests of reduction in structural loads and increasing energy production is the goal of a wind turbine controller to reduce the cost of producing wind energy. Conventional wind turbines use feedback methods to optimize these goals, reacting to wind disturbances after they have already impacted the wind turbine. Lidar sensors offer a means to provide additional inputs to a wind turbine controller, enabling new techniques to improve control methods, allowing a controller to actuate a wind turbine in anticipation of an incoming wind disturbance. This paper will look at the development of lidar-enhanced controls and how they have been used for various turbine load reductions with pitch actuation, as well as increased energy production with improved yaw control. Ongoing work will also be discussed to show that combining pitch and torque control using feedforward nonlinear model predictive control can lead to both reduced loads and increased energy production. Future work is also proposed on extending individual wind turbine controls to the wind plant level and determining how lidars can be used for control methods to further lower the cost of wind energy by minimizing wake impacts in a wind farm.
Building Chinese wind data for Wind Erosion Prediction System using surrogate US data
Wind erosion is a global problem, especially in arid and semiarid regions of the world, which leads to land degradation and atmosphere pollution. The process-based Wind Erosion Prediction System (WEPS), developed by the USDA, is capable of simulating the windblown soil loss with changing weather and...
Robust Model Predictive Control of a Wind Turbine
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2012-01-01
In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...
Energy Technology Data Exchange (ETDEWEB)
Odo, F.C. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria); Department of Physics and Astronomy, University of Nigeria, Nsukka (Nigeria); Akubue, G.U.; Offiah, S.U.; Ugwuoke, P.E. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria)
2013-07-01
In this paper, we use the correlation between the average wind speed and ambient temperature to develop models for predicting wind potentials for two Nigerian locations. Assuming that the troposphere is a typical heterogeneous mixture of ideal gases, we find that for the studied locations, wind speed clearly correlates with ambient temperature in a simple polynomial of 3rd degree. The coefficient of determination and root-mean-square error of the models are 0.81; 0.0024 and 0.56; 0.0041, respectively, for Enugu (6.40N; 7.50E) and Owerri (5.50N; 7.00E). These results suggest that the temperature-based model can be used, with acceptable accuracy, in predicting wind potentials needed for preliminary design assessment of wind energy conversion devices for the locations and others with similar meteorological conditions.
Catastrophic wind damage to North American forests and the potential impact of climate change
Energy Technology Data Exchange (ETDEWEB)
Peterson, C.J. [Department of Botany, 2502 Plant Sciences Building, University of Georgia, Athens, GA 30602-7271 (United States)
2000-11-15
incomplete, and climate-change model predictions sufficiently coarse, that predictions of changes in frequency, size, intensity, or timing of these extreme events must be regarded as highly uncertain. Moreover, retrospective approaches that employ tree demography and dendrochronology require prohibitively large sample sizes to resolve details of the relationship between climate fluctuations and characteristics of these storms. To improve predictions of changes in the climatology of these storms, we need improved understanding of the genesis of tornadoes and downbursts within thunderstorms, and greater resolution in global climate models. To improve coping strategies, forest scientists can contribute by giving more attention to how various silvicultural actions influence stand and tree vulnerability. Finally, increased focus on the dynamics of forest recovery and regrowth may suggest management actions that can facilitate desired objectives after one of these unpredictable wind disturbances.
Error analysis of short term wind power prediction models
International Nuclear Information System (INIS)
De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco
2011-01-01
The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)
Error analysis of short term wind power prediction models
Energy Technology Data Exchange (ETDEWEB)
De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)
2011-04-15
The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)
Short-term prediction method of wind speed series based on fractal interpolation
International Nuclear Information System (INIS)
Xiu, Chunbo; Wang, Tiantian; Tian, Meng; Li, Yanqing; Cheng, Yi
2014-01-01
Highlights: • An improved fractal interpolation prediction method is proposed. • The chaos optimization algorithm is used to obtain the iterated function system. • The fractal extrapolate interpolation prediction of wind speed series is performed. - Abstract: In order to improve the prediction performance of the wind speed series, the rescaled range analysis is used to analyze the fractal characteristics of the wind speed series. An improved fractal interpolation prediction method is proposed to predict the wind speed series whose Hurst exponents are close to 1. An optimization function which is composed of the interpolation error and the constraint items of the vertical scaling factors in the fractal interpolation iterated function system is designed. The chaos optimization algorithm is used to optimize the function to resolve the optimal vertical scaling factors. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Simulation results show that the fractal interpolation prediction method can get better prediction result than others for the wind speed series with the fractal characteristic, and the prediction performance of the proposed method can be improved further because the fractal characteristic of its iterated function system is similar to that of the predicted wind speed series
Tatarko, John; Sporcic, Michael A.; Skidmore, Edward L.
2013-09-01
The Great Plains experienced an influx of settlers in the late 1850s-1900. Periodic drought was hard on both settlers and the soil and caused severe wind erosion. The period known as the Dirty Thirties, 1931-1939, produced many severe windstorms, and the resulting dusty sky over Washington, DC helped Hugh Hammond Bennett gain political support for the Soil Conservation Act of 1937 that started the USDA Soil Conservation Service (SCS). Austin W. Zingg and William S. Chepil began wind erosion studies at a USDA laboratory at Kansas State University in 1947. Neil P. Woodruff and Francis H. Siddoway published the first widely used model for wind erosion in 1965, called the Wind Erosion Equation (WEQ). The WEQ was solved using a series of charts and lookup tables. Subsequent improvements to WEQ included monthly magnitudes of the total wind, a computer version of WEQ programmed in FORTRAN, small-grain equivalents for range grasses, tillage systems, effects of residue management, crop row direction, cloddiness, monthly climate factors, and the weather. The SCS and the Natural Resources Conservation Service (NRCS) produced several computer versions of WEQ with the goal of standardizing and simplifying it for field personnel including a standalone version of WEQ was developed in the late 1990s using Microsoft Excel. Although WEQ was a great advancement to the science of prediction and control of wind erosion on cropland, it had many limitations that prevented its use on many lands throughout the United States and the world. In response to these limitations, the USDA developed a process-based model know as the Wind Erosion Prediction System (WEPS). The USDA Agricultural Research Service has taken the lead in developing science and technology for wind erosion prediction.
A neuro-fuzzy controlling algorithm for wind turbine
Energy Technology Data Exchange (ETDEWEB)
Lin, Li [Tampere Univ. of Technology (Finland); Eriksson, J T [Tampere Univ. of Technology (Finland)
1996-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
A neuro-fuzzy controlling algorithm for wind turbine
Energy Technology Data Exchange (ETDEWEB)
Li Lin [Tampere Univ. of Technology (Finland); Eriksson, J.T. [Tampere Univ. of Technology (Finland)
1995-12-31
The wind turbine control system is stochastic and nonlinear, offering a demanding field for different control methods. An improved and efficient controller will have great impact on the cost-effectiveness of the technology. In this article, a design method for a self-organizing fuzzy controller is discussed, which combines two popular computational intelligence techniques, neural networks and fuzzy logic. Based on acquisited dynamic parameters of the wind, it can effectively predict wind changes in speed and direction. Maximum power can always be extracted from the kinetic energy of the wind. Based on the stimulating experiments applying nonlinear dynamics to a `Variable Speed Fixed Angle` wind turbine, it is demonstrated that the proposed control model 3rd learning algorithm provide a predictable, stable and accurate performance. The robustness of the controller to system parameter variations and measurement disturbances is also discussed. (author)
Model-based control of a ballast-stabilized floating wind turbine exposed to wind and waves
Energy Technology Data Exchange (ETDEWEB)
Christiansen, Soeren
2013-01-15
The wind turbine is a commercial product which is competing against other sources of energy, such as coal and gas. This competition drives a constant development to reduce costs and improve efficiency in order to reduce the total cost of the energy. The latest offshore development is the floating wind turbine, for water depths beyond 50 meters where winds are stronger and less turbulent. A floating wind turbine is subject to not only aerodynamics and wind induced loads, but also to hydrodynamics and wave induced loads. In contrast to a bottom fixed wind turbine, the floating structure, the hydrodynamics and the loads change the dynamic behavior of a floating wind turbine. Consequently, conventional wind turbine control cause instabilities on floating wind turbines. This work addresses the control of a floating spar buoy wind turbine, and focuses on the impact of the additional platform dynamics. A time varying control model is presented based on the wind speed and wave frequency. Estimates of the wind speed and wave frequency are used as scheduling variables in a gain scheduled linear quadratic controller to improve the electrical power production while reducing fatigue. To address the problem of negative damped fore-aft tower motion, additional control loops are suggested which stabilize the response of the onshore controller and reduce the impact of the wave induced loads. This research is then extended to model predictive control, to further address wave disturbances. In the context of control engineering, the dynamics and disturbances of a floating wind turbine have been identified and modeled. The objectives of maximizing the production of electrical power and minimizing fatigue have been reached by using advanced methods of estimation and control. (Author)
An adaptive short-term prediction scheme for wind energy storage management
International Nuclear Information System (INIS)
Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois
2011-01-01
Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.
Three-model ensemble wind prediction in southern Italy
Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo
2016-03-01
Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.
Development of Wind Farm AEP Prediction Program Considering Directional Wake Effect
Energy Technology Data Exchange (ETDEWEB)
Yang, Kyoungboo; Cho, Kyungho; Huh, Jongchul [Jeju Nat’l Univ., Jeju (Korea, Republic of)
2017-07-15
For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.
Siting wind farms in and around forests
Energy Technology Data Exchange (ETDEWEB)
Douglas, N. [Natural Power Consultants, Vancouver, BC (Canada)
2010-07-01
This PowerPoint presentation discussed methods of assessing the impact of trees on wind resources. Turbulence is generated and also absorbed by trees. Disturbances generated at tree level are then transported upwards and down-wind by the wind. The turbulence induced by trees can be felt kilometers downwind of forests at wind turbine hub heights. Wind speeds can be less than predicted, and significant over-estimations can occur with modelled results. The effects of high shear and high turbulence can also have an impact on power curve performance and lead to higher levels of mechanical stress. A SCADA analysis was used to demonstrate the impact of forests on power curves. Wind power predictions near forests can be optimized by using a full year of data capture at hub height, full rotor measurements, and a consideration of seasonal variations. Accurate tree maps are needed to determine the effects of trees on wind shear. Various forestry scenarios were modelled to demonstrate the effects of forestry management over time. tabs., figs.
Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity
Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick
2013-01-01
Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.
WPPT, a tool for on-line wind power prediction
Energy Technology Data Exchange (ETDEWEB)
Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)
2004-07-01
This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)
Directory of Open Access Journals (Sweden)
Ariel Santos Fuentefria
2015-04-01
Full Text Available El Límite de Potencia Eólica (LPE es la cantidad de potencia eólica que permite un sistema sin perder la estabilidad y depende principalmente de las características de los generadores eólicos y de las características del sistema en términos de debilidad. Conocer el comportamiento del sistema en régimen transitorio es sumamente importante; entre las condiciones que generan mayores problemas se encuentran el cortocircuito en las líneas de mayor transferencia de potenciay la salida de algún generador del sistema. El LPE cambia para cada condición y conocer el LPE considerando estas condiciones permite aprovechar al máximo la energía del viento. En el presente trabajo se analiza el comportamiento de generadores eólicos de velocidad fija para diversas condiciones transitorias de la red, utilizándose el sistema de prueba de 14 nodos de la IEEE para verificar la metodología en uso para el análisis a través de simulaciones implementadas en el software libre PSAT. The amount of wind power that allow an electric network without losing his stability as known as wind power limit. The wind power limit fundamentally depends on the wind turbine technology and the weakness level of the system. To know the system behaviors in dynamic performance having into account the worst disturbance is a very important matter, a short circuit in one of the most power transference line or the loss of a large generation unit was a large disturbance that can affect system stability. The wind power limit may change with the nature of the disturbance. To know the wind power limit considering this conditions allow use the wind at maximum level. In the present paper the behavior of fixed speed wind turbine for different fault types is analyzed, at those conditions, the wind power is increasing until the system become voltage unstable. For the analysis the IEEE 14 Bus Test Case is used. The Power System Analysis Toolbox (PSAT package is used for the simulation.
Directory of Open Access Journals (Sweden)
Ariel Santos Fuentefria
2014-06-01
Full Text Available El Límite de Potencia Eólica (LPE es la cantidad de potencia eólica que permite un sistema sin perder la estabilidad y depende principalmente de las características de los generadores eólicos y de las características del sistema en términos de debilidad. Conocer el comportamiento del sistema en régimen transitorio es sumamente importante; entre las condiciones que generan mayores problemas se encuentran el cortocircuito en las líneas de mayor transferencia de potenciay la salida de algún generador del sistema. El LPE cambia para cada condición y conocer el LPE considerando estas condiciones permite aprovechar al máximo la energía del viento. En el presente trabajo se analiza el comportamiento de generadores eólicos de velocidad fija para diversas condiciones transitorias de la red, utilizándose el sistema de prueba de 14 nodos de la IEEE para verificar la metodología en uso para el análisis a través de simulaciones implementadas en el software libre PSAT The amount of wind power that allow an electric network without losing his stability as known as wind power limit. The wind power limit fundamentally depends on the wind turbine technology and the weakness level of the system. To know the system behaviors in dynamic performance having into account the worst disturbance is a very important matter, a short circuit in one of the most power transference line or the loss of a large generation unit was a large disturbance that can affect system stability. The wind power limit may change with the nature of the disturbance. To know the wind power limit considering this conditions allow use the wind at maximum level. In the present paper the behavior of fixed speed wind turbine for different fault types is analyzed, at those conditions, the wind power is increasing until the system become voltage unstable. For the analysis the IEEE 14 Bus Test Case is used. The Power System Analysis Toolbox (PSAT package is used for the simulation.
Jalali, Leila; Nezhad-Ahmadi, Mohammad-Reza; Gohari, Mahmood; Bigelow, Philip; McColl, Stephen
2016-07-01
Canada's wind energy capacity has grown from approximately 137MW (MW) in 2000 to over 9700MW in 2014, and this progressive development has made Canada the fifth-largest market in the world for the installation of new wind turbines (WTs). Although wind energy is now one of the fastest growing sources of power in Canada and many other countries, the growth in both number and size of WTs has raised questions regarding potential health impacts on individuals who live close to such turbines. This study is the first published research using a prospective cohort design, with noise and sleep measurements obtained before and after installation of WTs to investigate effect of such turbines on self-reported sleep disturbances of nearby residents. Subjective assessment of sleep disturbance was conducted in Ontario, Canada through standard sleep and sleepiness scales, including the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and Epworth daytime Sleepiness Scale (ESS). Both audible and infra-sound noises were also measured inside the bedroom. Descriptive and comparison analyses were performed to investigate the effect of WT exposure on sleep data. Results of the analysis show that participants reported poorer sleep quality if they had a negative attitude to WTs, if they had concerns related to property devaluation, and if they could see turbines from their properties. This study provides evidence for the role of individual differences and psychological factors in reports of sleep disturbance by people living in the vicinity of WTs. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
Spatial mapping and attribution of Wyoming wind turbines
O'Donnell, Michael S.; Fancher, Tammy S.
2010-01-01
This Wyoming wind-turbine data set represents locations of wind turbines found within Wyoming as of August 1, 2009. Each wind turbine is assigned to a wind farm. For each turbine, this report contains information about the following: potential megawatt output, rotor diameter, hub height, rotor height, land ownership, county, wind farm power capacity, the number of units currently associated with its wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some attributes are estimates based on information that was obtained through the American Wind Energy Association and miscellaneous online reports. The locations are derived from August 2009 true-color aerial photographs made by the National Agriculture Imagery Program; the photographs have a positional accuracy of approximately ?5 meters. The location of wind turbines under construction during the development of this data set will likely be less accurate than the location of turbines already completed. The original purpose for developing the data presented here was to evaluate the effect of wind energy development on seasonal habitat used by greater sage-grouse. Additionally, these data will provide a planning tool for the Wyoming Landscape Conservation Initiative Science Team and for other wildlife- and habitat-related projects underway at the U.S. Geological Survey's Fort Collins Science Center. Specifically, these data will be used to quantify disturbance of the landscape related to wind energy as well as quantifying indirect disturbances to flora and fauna. This data set was developed for the 2010 project 'Seasonal predictive habitat models for greater sage-grouse in Wyoming.' This project's spatially explicit seasonal distribution models of sage-grouse in Wyoming will provide resource managers with tools for conservation planning. These
Short-term prediction of local wind conditions
DEFF Research Database (Denmark)
Landberg, L.
2001-01-01
This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual...
Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures
de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.
2012-01-01
Background: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topo...
Cathryn H. Greenberg
2001-01-01
Reptile and amphibian communities were sampled in intact gaps created by wind disturbance, salvage-logged gaps, and closed canopy mature forest (controls). Sampling was conducted during JuneâOctober in 1997 and 1998 using drift fences with pitfall and funnel traps. Basal area of live trees, shade, leaf litter coverage, and litter depth was highest in controls and...
Verification of some numerical models for operationally predicting mesoscale winds aloft
International Nuclear Information System (INIS)
Cornett, J.S.; Randerson, D.
1977-01-01
Four numerical models are described for predicting mesoscale winds aloft for a 6 h period. These models are all tested statistically against persistence as the control forecast and against predictions made by operational forecasters. Mesoscale winds aloft data were used to initialize the models and to verify the predictions on an hourly basis. The model yielding the smallest root-mean-square vector errors (RMSVE's) was the one based on the most physics which included advection, ageostrophic acceleration, vertical mixing and friction. Horizontal advection was found to be the most important term in reducing the RMSVE's followed by ageostrophic acceleration, vertical advection, surface friction and vertical mixing. From a comparison of the mean absolute errors based on up to 72 independent wind-profile predictions made by operational forecasters, by the most complete model, and by persistence, we conclude that the model is the best wind predictor in the free air. In the boundary layer, the results tend to favor the forecaster for direction predictions. The speed predictions showed no overall superiority in any of these three models
Load prediction of stall regulated wind turbines
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A.; Dahlberg, J.Aa. [Aeronautical Research Inst. of Sweden, Bromma (Sweden); Carlen, I. [Chalmers Univ. of Technology, Goeteborg (Sweden). Div. of Marine Structural Engineering; Ganander, H. [Teknikgruppen AB, Sollentua (Sweden)
1996-12-01
Measurements of blade loads on a turbine situated in a small wind farm shows that the highest blade loads occur during operation close to the peak power i.e. when the turbine operates in the stall region. In this study the extensive experimental data base has been utilised to compare loads in selected campaigns with corresponding load predictions. The predictions are based on time domain simulations of the wind turbine structure, performed by the aeroelastic code VIDYN. In the calculations a model were adopted in order to include the effects of dynamic stall. This paper describes the work carried out so far within the project and key results. 5 refs, 10 figs
The state of the art of predicting noise-induced sleep disturbance in field settings
Sanford Fidell; Barbara Tabachnick; Karl S Pearsons
2010-01-01
Several relationships between intruding noises (largely aircraft) and sleep disturbance have been inferred from the findings of a handful of field studies. Comparisons of sleep disturbance rates predicted by the various relationships are complicated by inconsistent data collection methods and definitions of predictor variables and predicted quantities. None of the relationships is grounded in theory-based understanding, and some depend on questionable statistical assumptions and analysis proc...
Selection of References in Wind Turbine Model Predictive Control Design
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Hovgaard, Tobias
2015-01-01
a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...
Prediction of Wind Energy Resources (PoWER) Users Guide
2016-01-01
ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...manufacturer’s or trade names does not constitute an official endorsement or approval of the use thereof. Destroy this report when it is no longer needed. Do...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER
Grib, S. A.; Leora, S. N.
2016-03-01
We use analytical methods of magnetohydrodynamics to describe the behavior of cosmic plasma. This approach makes it possible to describe different structural fields of disturbances in solar wind: shock waves, direction discontinuities, magnetic clouds and magnetic holes, and their interaction with each other and with the Earth's magnetosphere. We note that the wave problems of solar-terrestrial physics can be efficiently solved by the methods designed for solving classical problems of mathematical physics. We find that the generalized Riemann solution particularly simplifies the consideration of secondary waves in the magnetosheath and makes it possible to describe in detail the classical solutions of boundary value problems. We consider the appearance of a fast compression wave in the Earth's magnetosheath, which is reflected from the magnetosphere and can nonlinearly overturn to generate a back shock wave. We propose a new mechanism for the formation of a plateau with protons of increased density and a magnetic field trough in the magnetosheath due to slow secondary shock waves. Most of our findings are confirmed by direct observations conducted on spacecrafts (WIND, ACE, Geotail, Voyager-2, SDO and others).
Predicting annoyance by wind turbine noise
Janssen, S.A.; Vos, H.; Eisses, A.R.; Pedersen, E.
2010-01-01
While wind turbines have beneficial effects for the environment, they inevitably generate environmental noise. In order to protect residents against unacceptable levels of noise, exposure-response relationships are needed to predict the expected percentage of people annoyed or highly annoyed at a
International Nuclear Information System (INIS)
Sun, W.; Akasofu, S.-I.; Smith, Z.K.; Dryer, M.
1985-01-01
An empirical kinematic method developed by Hakamada and Akasofu (1982) is calibrated on the basis of a one-dimensional MHD solution. The calibrated results are used to simulate the stream-stream interaction and the background corotating structure in a simple situation and also during 22 November-6 December 1977. The solar wind disturbances caused by solar activities during this period are then introduced into the above background stream in simulating the heliospheric disturbance event which was observed by an aligned set of spacecraft at distances between 0.6 and 1.6 a.u. The observations and the simulated results are satisfactory, and a little more refinement in the simulation could reconstruct reasonably well the data by filling the data gaps in the solar wind speed, the density and the IMF magnitude. (author)
Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad
2013-01-01
, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based......The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...
Energy Technology Data Exchange (ETDEWEB)
Lee, Gwang-Se; Cheong, Cheolung, E-mail: ccheong@pusan.ac.kr [School of Mechanical Engineering, Pusan National University, Busan, 609-745, Rep. of Korea (Korea, Republic of)
2014-12-15
Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.
Directory of Open Access Journals (Sweden)
Gwang-Se Lee
2014-12-01
Full Text Available Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs, few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.
Directory of Open Access Journals (Sweden)
L. Lyubchik
2009-01-01
Full Text Available The problem of disturbances forecasting in vehicles control systems is considered in the given article. On the basis of nuclear campaign recurrence there have been obtained algorithms of identification and prediction of disturbances time series.
A new ensemble model for short term wind power prediction
DEFF Research Database (Denmark)
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...
The Impact of Variable Wind Shear Coefficients on Risk Reduction of Wind Energy Projects.
Corscadden, Kenneth W; Thomson, Allan; Yoonesi, Behrang; McNutt, Josiah
2016-01-01
Estimation of wind speed at proposed hub heights is typically achieved using a wind shear exponent or wind shear coefficient (WSC), variation in wind speed as a function of height. The WSC is subject to temporal variation at low and high frequencies, ranging from diurnal and seasonal variations to disturbance caused by weather patterns; however, in many cases, it is assumed that the WSC remains constant. This assumption creates significant error in resource assessment, increasing uncertainty in projects and potentially significantly impacting the ability to control gird connected wind generators. This paper contributes to the body of knowledge relating to the evaluation and assessment of wind speed, with particular emphasis on the development of techniques to improve the accuracy of estimated wind speed above measurement height. It presents an evaluation of the use of a variable wind shear coefficient methodology based on a distribution of wind shear coefficients which have been implemented in real time. The results indicate that a VWSC provides a more accurate estimate of wind at hub height, ranging from 41% to 4% reduction in root mean squared error (RMSE) between predicted and actual wind speeds when using a variable wind shear coefficient at heights ranging from 33% to 100% above the highest actual wind measurement.
A new approach to very short term wind speed prediction using k-nearest neighbor classification
International Nuclear Information System (INIS)
Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami
2013-01-01
Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric
Hourly Wind Speed Interval Prediction in Arid Regions
Chaouch, M.; Ouarda, T.
2013-12-01
context, probabilistic forecasts might be more relevant than point forecasts for the planner to build scenarios In this paper, we are interested in estimating predictive intervals of the hourly wind speed measures in few cities in United Arab emirates (UAE). More precisely, given a wind speed time series, our target is to forecast the wind speed at any specific hour during the day and provide in addition an interval with the coverage probability 0flexible because it does not need a specification of the model to work with (such as normal distribution or a linear relation). Here, we use a covariable that is correlated to the wind speed. In practice, many possible choices of the covariate are available. In fact, in addition to its historical data, the wind speed is highly correlated to temperature, humidity and wind direction. In this paper a comparison, in terms of Mean Absolute Prediction Errors and Interquartile Range, between those choices will be provided to show which covariates are more suitable to forecast wind speed.
Model Predictive Voltage Control of Wind Power Plants
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei
2018-01-01
the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...
Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.
Ak, Ronay; Fink, Olga; Zio, Enrico
2016-08-01
The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.
Artificial intelligence to predict short-term wind speed
Energy Technology Data Exchange (ETDEWEB)
Pinto, Tiago; Soares, Joao; Ramos, Sergio; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - ISEP
2012-07-01
The use of renewable energy is increasing exponentially in many countries due to the introduction of new energy and environmental policies. Thus, the focus on energy and on the environment makes the efficient integration of renewable energy into the electric power system extremely important. Several European countries have been seeing a high penetration of wind power, representing, gradually, a significant penetration on electricity generation. The introduction of wind power in the network power system causes new challenges for the power system operator due to the variability and uncertainty in weather conditions and, consequently, in the wind power generation. As result, the scheduling dispatch has a significantly portion of uncertainty. In order to deal with the uncertainty in wind power and, with that, introduce improvements in the power system operator efficiency, the wind power forecasting may reveal as a useful tool. This paper proposes a data-mining-based methodology to forecast wind speed. This method is based on the use of data mining techniques applied to a real database of historical wind data. The paper includes a case study based on a real database regarding the last three years to predict wind speed at 5 minute intervals. (orig.)
Disturbance Regimes Predictably Alter Diversity in an Ecologically Complex Bacterial System
Directory of Open Access Journals (Sweden)
Sean M. Gibbons
2016-12-01
Full Text Available Diversity is often associated with the functional stability of ecological communities from microbes to macroorganisms. Understanding how diversity responds to environmental perturbations and the consequences of this relationship for ecosystem function are thus central challenges in microbial ecology. Unimodal diversity-disturbance relationships, in which maximum diversity occurs at intermediate levels of disturbance, have been predicted for ecosystems where life history tradeoffs separate organisms along a disturbance gradient. However, empirical support for such peaked relationships in macrosystems is mixed, and few studies have explored these relationships in microbial systems. Here we use complex microbial microcosm communities to systematically determine diversity-disturbance relationships over a range of disturbance regimes. We observed a reproducible switch between community states, which gave rise to transient diversity maxima when community states were forced to mix. Communities showed reduced compositional stability when diversity was highest. To further explore these dynamics, we formulated a simple model that reveals specific regimes under which diversity maxima are stable. Together, our results show how both unimodal and non-unimodal diversity-disturbance relationships can be observed as a system switches between two distinct microbial community states; this process likely occurs across a wide range of spatially and temporally heterogeneous microbial ecosystems.
Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.
2010-12-01
Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on
PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC
Directory of Open Access Journals (Sweden)
Altab Hossain
2009-01-01
Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.
PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC
Directory of Open Access Journals (Sweden)
Altab Md. Hossain
2009-12-01
Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.
The solar wind-magentosphere energy coupling and magnetospheric disturbances
International Nuclear Information System (INIS)
Akasofu, S.I.
1980-01-01
The recent finding of the solar wind-magnetosphere energy coupling function epsilon has advanced significantly our understanding of magnetosphere disturbances. It is shown that the magnetosphere-ionosphere coupling system responds somewhat differently to three different input energy flux levels of epsilon. As epsilon increases from 17 erg s -1 to >10 19 erg s -1 , typical responses of the magnetosphere-ionosphere coupling system are: (1) epsilon 17 erg s -1 : an enhancement of the Ssub(q)sup(p), etc. (2) epsilon approximately 10 18 erg s -1 : substorm onset. (3) 10 18 erg s -1 19 erg s -1 : a typical substorm. (4) epsilon >10 19 erg s -1 : an abnormal growth of the ring current belt, resulting in a magnetospheric storm. It is stressed that the magnetospheric substorm results as a direct response of the magnetosphere to a rise and fall of epsilon above approximately 10 18 erg s -1 , so that it is not caused by a sudden conversion of magnetic energy accumulated prior to substorm onset. The variety of the development of the main phase of geomagnetic storms is also primarily controlled by epsilon. (author)
Estimation of wind erosion from construction of a railway in arid Northwest China
Directory of Open Access Journals (Sweden)
Benli Liu
2017-06-01
Full Text Available A state-of-the-art wind erosion simulation model, the Wind Erosion Prediction System and the United States Environmental Protection Agency's AP 42 emission factors formula, were combined together to evaluate wind-blown dust emissions from various construction units from a railway construction project in the dry Gobi land in Northwest China. The influence of the climatic factors: temperature, precipitation, wind speed and direction, soil condition, protective measures, and construction disturbance were taken into account. Driven by daily and sub-daily climate data and using specific detailed management files, the process-based WEPS model was able to express the beginning, active, and ending phases of construction, as well as the degree of disturbance for the entire scope of a construction project. The Lanzhou-Xinjiang High-speed Railway was selected as a representative study because of the diversities of different climates, soil, and working schedule conditions that could be analyzed. Wind erosion from different working units included the building of roadbeds, bridges, plants, temporary houses, earth spoil and barrow pit areas, and vehicle transportation were calculated. The total wind erosion emissions, 7406 t, for the first construction area of section LXS-15 with a 14.877 km length was obtained for quantitative analysis. The method used is applicable for evaluating wind erosion from other complex surface disturbance projects.
Directory of Open Access Journals (Sweden)
Dongmyung Kim
2018-05-01
Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.
Research on wind field algorithm of wind lidar based on BP neural network and grey prediction
Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei
2018-01-01
This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.
International Nuclear Information System (INIS)
Wu, Xuedong; Zhu, Zhiyu; Su, Xunliang; Fan, Shaosheng; Du, Zhaoping; Chang, Yanchao; Zeng, Qingjun
2015-01-01
Wind speed prediction is one important methods to guarantee the wind energy integrated into the whole power system smoothly. However, wind power has a non–schedulable nature due to the strong stochastic nature and dynamic uncertainty nature of wind speed. Therefore, wind speed prediction is an indispensable requirement for power system operators. Two new approaches for hourly wind speed prediction are developed in this study by integrating the single multiplicative neuron model and the iterated nonlinear filters for updating the wind speed sequence accurately. In the presented methods, a nonlinear state–space model is first formed based on the single multiplicative neuron model and then the iterated nonlinear filters are employed to perform dynamic state estimation on wind speed sequence with stochastic uncertainty. The suggested approaches are demonstrated using three cases wind speed data and are compared with autoregressive moving average, artificial neural network, kernel ridge regression based residual active learning and single multiplicative neuron model methods. Three types of prediction errors, mean absolute error improvement ratio and running time are employed for different models’ performance comparison. Comparison results from Tables 1–3 indicate that the presented strategies have much better performance for hourly wind speed prediction than other technologies. - Highlights: • Developed two novel hybrid modeling methods for hourly wind speed prediction. • Uncertainty and fluctuations of wind speed can be better explained by novel methods. • Proposed strategies have online adaptive learning ability. • Proposed approaches have shown better performance compared with existed approaches. • Comparison and analysis of two proposed novel models for three cases are provided
Model predictive control of wind energy conversion systems
Yaramasu, Venkata Narasimha R
2017-01-01
The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.
A first generation numerical geomagnetic storm prediction scheme
International Nuclear Information System (INIS)
Akasofu, S.-I.; Fry, C.F.
1986-01-01
Because geomagnetic and auroral disturbances cause significant interference on many electrical systems, it is essential to develop a reliable geomagnetic and auroral storm prediction scheme. A first generation numerical prediction scheme has been developed. The scheme consists of two major computer codes which in turn consist of a large number of subroutine codes and of empirical relationships. First of all, when a solar flare occurs, six flare parameters are determined as the input data set for the first code which is devised to show the simulated propagation of solar wind disturbances in the heliosphere to a distance of 2 a.u. Thus, one can determine the relative location of the propagating disturbances with the Earth's position. The solar wind speed and the three interplanetary magnetic field (IMF) components are then computed as a function of time at the Earth's location or any other desired (space probe) locations. These quantities in turn become the input parameters for the second major code which computes first the power of the solar wind-magnetosphere dynamo as a function of time. The power thus obtained and the three IMF components can be used to compute or infer: the predicted geometry of the auroral oval; the cross-polar cap potential; the two geomagnetic indices AE and Dst; the total energy injection rate into the polar ionosphere; and the atmospheric temperature, etc. (author)
Vertical Wind Tunnel for Prediction of Rocket Flight Dynamics
Directory of Open Access Journals (Sweden)
Hoani Bryson
2016-03-01
Full Text Available A customized vertical wind tunnel has been built by the University of Canterbury Rocketry group (UC Rocketry. This wind tunnel has been critical for the success of UC Rocketry as it allows the optimization of avionics and control systems before flight. This paper outlines the construction of the wind tunnel and includes an analysis of flow quality including swirl. A minimal modelling methodology for roll dynamics is developed that can extrapolate wind tunnel behavior at low wind speeds to much higher velocities encountered during flight. The models were shown to capture the roll flight dynamics in two rocket launches with mean roll angle errors varying from 0.26° to 1.5° across the flight data. The identified model parameters showed consistent and predictable variations over both wind tunnel tests and flight, including canard–fin interaction behavior. These results demonstrate that the vertical wind tunnel is an important tool for the modelling and control of sounding rockets.
DEFF Research Database (Denmark)
Troen, Ib; Bechmann, Andreas; Kelly, Mark C.
2014-01-01
Using the Wind Atlas methodology to predict the average wind speed at one location from measured climatological wind frequency distributions at another nearby location we analyse the relative prediction errors using a linearized flow model (IBZ) and a more physically correct fully non-linear 3D...... flow model (CFD) for a number of sites in very complex terrain (large terrain slopes). We first briefly describe the Wind Atlas methodology as implemented in WAsP and the specifics of the “classical” model setup and the new setup allowing the use of the CFD computation engine. We discuss some known...
Sleep disturbances predict prospective declines in resident physicians’ psychological well-being
Directory of Open Access Journals (Sweden)
Alice A. Min
2015-07-01
Full Text Available Background: Medical residency can be a time of increased psychological stress and sleep disturbance. We examine the prospective associations between self-reported sleep quality and resident wellness across a single training year. Methods: Sixty-nine (N=69 resident physicians completed the Brief Resident Wellness Profile (M=17.66, standard deviation [SD]=3.45, range: 0–17 and the Pittsburgh Sleep Quality Index (M=6.22, SD=2.86, range: 12–25 at multiple occasions in a single training year. We examined the 1-month lagged effect of sleep disturbances on residents’ self-reported wellness. Results: Accounting for residents’ overall level of sleep disturbance across the entire study period, both the concurrent (within-person within-occasion effect of sleep disturbance (B=−0.20, standard error [SE]=0.06, p=0.003, 95% confidence interval [CI]: −0.33, −0.07 and the lagged within-person effect of resident sleep disturbance (B=−0.15, SE=0.07, p=0.037, 95% CI: −0.29, −0.009 were significant predictors of decreased resident wellness. Increases in sleep disturbances are a leading indicator of resident wellness, predicting decreased well-being 1 month later. Conclusions: Sleep quality exerts a significant effect on self-reported resident wellness. Periodic evaluation of sleep quality may alert program leadership and the residents themselves to impending decreases in psychological well-being.
Abdullahi, Auwalu M.; Mohamed, Z.; Selamat, H.; Pota, Hemanshu R.; Zainal Abidin, M. S.; Ismail, F. S.; Haruna, A.
2018-01-01
Payload hoisting and wind disturbance during crane operations are among the challenging factors that affect a payload sway and thus, affect the crane's performance. This paper proposes a new online adaptive output-based command shaping (AOCS) technique for an effective payload sway reduction of an overhead crane under the influence of those effects. This technique enhances the previously developed output-based command shaping (OCS) which was effective only for a fixed system and without external disturbances. Unlike the conventional input shaping design technique which requires the system's natural frequency and damping ratio, the proposed technique is designed by using the output signal and thus, an online adaptive algorithm can be formulated. To test the effectiveness of the AOCS, experiments are carried out using a laboratory overhead crane with a payload hoisting in the presence of wind, and with different payloads. The superiority of the method is confirmed by 82% and 29% reductions in the overall sway and the maximum transient sway respectively, when compared to the OCS, and two robust input shapers namely Zero Vibration Derivative-Derivative and Extra-Insensitive shapers. Furthermore, the method demonstrates a uniform crane's performance under all conditions. It is envisaged that the proposed method can be very useful in designing an effective controller for a crane system with an unknown payload and under the influence of external disturbances.
Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft
Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei
2018-05-01
Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).
The statistical prediction of offshore winds from land-based data for wind-energy applications
DEFF Research Database (Denmark)
Walmsley, J.L.; Barthelmie, R.J.; Burrows, W.R.
2001-01-01
Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and for verification. As a first step, the two datasets were separated into nine...... percentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes....... The binning procedure ensured that both training and test sets fairly represented the overall data distribution. To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random...
Directory of Open Access Journals (Sweden)
Yolanda Vidal
2015-05-01
Full Text Available This paper develops a fault diagnosis (FD and fault-tolerant control (FTC of pitch actuators in wind turbines. This is accomplished by combining a disturbance compensator with a controller, both of which are formulated in the discrete time domain. The disturbance compensator has a dual purpose: to estimate the actuator fault (which is used by the FD algorithm and to design the discrete time controller to obtain an FTC. That is, the pitch actuator faults are estimated, and then, the pitch control laws are appropriately modified to achieve an FTC with a comparable behavior to the fault-free case. The performance of the FD and FTC schemes is tested in simulations with the aero-elastic code FAST.
Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette
2009-01-01
Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.
Predictability and Variability of Wave and Wind
DEFF Research Database (Denmark)
Chozas, Julia Fernandez; Kofoed, Jens Peter; Sørensen, Hans Christian
This project covers two fields of study: a) Wave energy predictability and electricity markets. b) Variability of the power output of WECs in diversified systems : diversified renewable systems with wave and offshore wind production. See page 2-4 in the report for a executive summery....
VT Predicted Mean Wind Speed - 70 meter height
Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 70m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...
VT Predicted Mean Wind Power - 50 meter height
Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...
VT Predicted Mean Wind Speed - 30 meter height
Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 30m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...
A new wind power prediction method based on chaotic theory and Bernstein Neural Network
International Nuclear Information System (INIS)
Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao
2016-01-01
The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.
Impact of wind turbines on birdlife
International Nuclear Information System (INIS)
Benner, J.H.B.; Berkhuizen, J.C.; De Graaff, R.J.; Postma, A.D.; Hendriks, J.H.W.
1993-05-01
An overview of wind energy programmes is presented, as well as an analysis of recent studies on the title subject and data on the attitude of nature conservation organisations both from the USA and Europe. The studies were analyzed for legitimacy of assumptions and validity of the conclusions. Most of the wind energy programs and all European studies deal with bird kills and disturbance in coastal areas. The number of victims per turbine per year in this type of area appears to be acceptable. The disturbing effect of wind turbines on breeding birds appears to be negligible. The disturbance of resting and migrating birds by wind turbines however is reasonably clear. As a result of international concern several sites have been designated where siting of wind turbines is prohibited. Well known examples are wetlands of international importance (Ramsar-convention) and European Community Special Protection Areas. Major concern among conservationists is the location of many valuable and vulnerable environmental resources outside the protected areas. Negative attitudes towards wind energy projects are not particularly due to avian considerations, but rather to a general objective to protect landscapes and habitats, undisturbed by human infrastructures and disturbance. It is concluded that all new locations for wind energy projects should be weighed on the disturbance aspect. Reference data for such a weigh are available for coastal areas, although the impact on local migration between feeding grounds and high water refugee areas needs further research. Future research is also needed for application of wind energy both on off-shore locations, grasslands and farmlands. Wind energy developers and conservationists should have a close contact in order to establish consensus on how to deal with remaining uncertainties. 7 figs., 9 tabs., 5 appendices, 37 refs
Impact of wind turbines on birdlife
Energy Technology Data Exchange (ETDEWEB)
Benner, J H.B.; Berkhuizen, J C; De Graaff, R J; Postma, A D [Consultants on Energy and Environment CEA, Rotterdam (Netherlands); Hendriks, J H.W. [Rijksuniversiteit Leiden (Netherlands)
1993-05-01
An overview of wind energy programmes is presented, as well as an analysis of recent studies on the title subject and data on the attitude of nature conservation organisations both from the USA and Europe. The studies were analyzed for legitimacy of assumptions and validity of the conclusions. Most of the wind energy programs and all European studies deal with bird kills and disturbance in coastal areas. The number of victims per turbine per year in this type of area appears to be acceptable. The disturbing effect of wind turbines on breeding birds appears to be negligible. The disturbance of resting and migrating birds by wind turbines however is reasonably clear. As a result of international concern several sites have been designated where siting of wind turbines is prohibited. Well known examples are wetlands of international importance (Ramsar-convention) and European Community Special Protection Areas. Major concern among conservationists is the location of many valuable and vulnerable environmental resources outside the protected areas. Negative attitudes towards wind energy projects are not particularly due to avian considerations, but rather to a general objective to protect landscapes and habitats, undisturbed by human infrastructures and disturbance. It is concluded that all new locations for wind energy projects should be weighed on the disturbance aspect. Reference data for such a weigh are available for coastal areas, although the impact on local migration between feeding grounds and high water refugee areas needs further research. Future research is also needed for application of wind energy both on off-shore locations, grasslands and farmlands. Wind energy developers and conservationists should have a close contact in order to establish consensus on how to deal with remaining uncertainties. 7 figs., 9 tabs., 5 appendices, 37 refs.
Laminar-Turbulent transition on Wind Turbines
DEFF Research Database (Denmark)
Martinez Hernandez, Gabriel Gerardo
The present thesis deals with the study of the rotational effects on the laminar-turbulent transition on wind turbine blades. Linear stability theory is used to formulate the stability equations that include the effect of rotation. The mean flow required as an input to stability computations...... parametrized and adapted to an wind turbine rotor geometry. The blade is resolved in radial sections along which calculations are performed. The obtained mean flow is classified according to the parameters used on the rotating configuration, geometry and operational conditions. The stability diagrams have been...... to define the resultant wave magnitude and direction. The propagation of disturbances in the boundary layers in three dimensional flows is relatively a complicated phenomena. The report discusses the available methods and techniques used to predict the transition location. Some common wind turbine airfoils...
Development of a wind farm noise propagation prediction model - project progress to date
International Nuclear Information System (INIS)
Robinson, P.; Bullmore, A.; Bass, J.; Sloth, E.
1998-01-01
This paper describes a twelve month measurement campaign which is part of a European project (CEC Project JOR3-CT95-0051) with the aim to substantially reduce the uncertainties involved in predicting environmentally radiated noise levels from wind farms (1). This will be achieved by comparing noise levels measure at varying distances from single and multiple sources over differing complexities of terrain with those predicted using a number of currently adopted sound propagation models. Specific objectives within the project are to: establish the important parameters controlling the propagation of wind farm noise to the far field; develop a planning tool for predicting wind farm noise emission levels under practically encountered conditions; place confidence limits on the upper and lower bounds of the noise levels predicted, thus enabling developers to quantify the risk whether noise emission from wind farms will cause nuisance to nearby residents. (Author)
Wind turbine control and model predictive control for uncertain systems
DEFF Research Database (Denmark)
Thomsen, Sven Creutz
as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...
International Nuclear Information System (INIS)
Niedner, M.B. Jr.; Brandt, J.C.; Zwickl, R.D.; Bame, S.J.
1982-01-01
Solar-wind plasma data from the ISEE-3 and Helios 2 spacecraft have been examined in order to explain a uniquely rapid 10 0 turning of the plasma tail of comet Bradfield 1979L on 1980 February 6. An earlier study conducted before the availability of in situ solar-wind data (Brandt et al., 1980) suggested that the tail position angle change occurred in response to a solar-wind velocity shear across which the polar component changed by approx. 50 km s - 1 . The present contribution confirms this result and further suggests that the comet-tail activity was caused by non-corotating, disturbed plasma flows probably associated with an Importance 1B solar flare
A methodology for the prediction of offshore wind energy resources
Energy Technology Data Exchange (ETDEWEB)
Watson, S J; Watson, G M [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Holt, R.J. [Univ. of East Anglia, Climatic Research Unit, Norwich (United Kingdom)] Barthelmie, R.J. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Zuylen, E.J. van [Ecofys Energy and Environment, Utrecht (Netherlands)] Cleijne, J.W. [Kema Sustainable, Arnhem (Netherlands)
1999-03-01
There are increasing constraints on the development of wind power on land. Recently, there has been a move to develop wind power offshore, though the amount of measured wind speed data at potential offshore wind farm sites is sparse. We present a novel methodology for the prediction of offshore wind power resources which is being applied to European Union waters. The first stage is to calculate the geostrophic wind from long-term pressure fields over the sea area of interest. Secondly, the geostrophic wind is transformed to the sea level using WA{sup s}P, taking account of near shore topography. Finally, these values are corrected for land/sea climatology (stability) effects using an analytical Coastal discontinuity Model (CDM). These values are further refined using high resolution offshore data at selected sites. The final values are validated against existing offshore datasets. Preliminary results are presented of the geostrophic wind speed validation in European Union waters. (au)
Directory of Open Access Journals (Sweden)
Laura Cornejo-Bueno
2017-11-01
Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.
A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction
Belu, Radian
2010-11-01
In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.
Wind and wildlife in the Northern Great Plains: identifying low-impact areas for wind development.
Directory of Open Access Journals (Sweden)
Joseph Fargione
Full Text Available Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW than most other forms of energy production and has known and predicted adverse effects on wildlife. The Northern Great Plains (NGP is home both to some of the world's best wind resources and to remaining temperate grasslands, the most converted and least protected ecological system on the planet. Thus, appropriate siting and mitigation of wind development is particularly important in this region. Steering energy development to disturbed lands with low wildlife value rather than placing new developments within large and intact habitats would reduce impacts to wildlife. Goals for wind energy development in the NGP are roughly 30 GW of nameplate capacity by 2030. Our analyses demonstrate that there are large areas where wind development would likely have few additional impacts on wildlife. We estimate there are ∼1,056 GW of potential wind energy available across the NGP on areas likely to have low-impact for biodiversity, over 35 times development goals. New policies and approaches will be required to guide wind energy development to low-impact areas.
Development of the Wind Erosion Prediction System (WEPS) was officially inaugurated in 1985 by United States Department of Agriculture-Agricultural Research Service (USDA-ARS) scientists in response to customer requests, particularly those coming from the USDA Soil Conservation Service (SCS), for im...
Deockho Kim; Jin Hur
2017-01-01
Due to the intermittency of wind power generation, it is very hard to manage its system operation and planning. In order to incorporate higher wind power penetrations into power systems that maintain secure and economic power system operation, an accurate and efficient estimation of wind power outputs is needed. In this paper, we propose the stochastic prediction of wind generating resources using an enhanced ensemble model for Jeju Island’s wind farms in South Korea. When selecting the poten...
Aerodynamic performance prediction of Darrieus-type wind turbines
Directory of Open Access Journals (Sweden)
Ion NILĂ
2010-06-01
Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.
Experiences of disturbance from wind power. Final report
International Nuclear Information System (INIS)
Pedersen, Eja
2002-02-01
Wind power generates electricity at low environmental costs, but local residents sometimes have had complains. To support further development of wind farms, it is important to find out if people are annoyed and if so, in what way. This is a preliminary study that will be followed by an extensive survey in Laholm, a municipality in the South of Sweden with 44 wind power turbines. A survey based on cases of complaints in Laholm shows that outdoor noise is the most common annoyance. Others are indoor noise, shadow flicker and visual impact. Residents in one nearby location, Falkenberg, that resembles the landscape in Laholm, were interviewed. The most common source of annoyance was traffic noise. The turbines annoyed no respondent, even thought the estimated noise levels in some cases exceeded the 40-dBA limit. Also in another location outside Halmstad people that lived close to the wind turbines experienced no problems. The number of people actually indicating annoyance by wind turbines is probably fairly small. The most common annoyance is that from wind turbine noise. People who are annoyed of noise could eater be exposed to higher noise levels than estimated or of certain discomforting type of noise. Several other factors of individual nature could also affect the annoyance. These are assumed to be the general attitude towards wind power, if you are in the possession of a turbine, if you are raised in the countryside or in a city, and the general attitude towards the authorities. Following these assumptions, several hypotheses for the main survey are discussed and described
Macwilkinson, D. G.; Blackerby, W. T.; Paterson, J. H.
1974-01-01
The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.
Zieger, Toni; Ritter, Joachim
2017-04-01
Within the scope of the project "TremAc", we present new insights of ground motion disturbances due to wind turbines (WTs) in the vicinity of the town of Landau, SW Germany. The main goal of this project, which is funded by the German Federal Ministry for Economic Affairs and Energy, is the detection of influences from WTs on human health and buildings in an interdisciplinary way. The interaction between WTs, humans, infrastructure (incl.seismic stations) becomes more and more an important role with the increase of installed WTs. We present averaged one hour long PSD-spectra in a frequency range from 0.5 Hz to 7 Hz depending on the wind speed before and after the installation of characteristic WTs, especially for seismic borehole stations, during one month measurements. The results show a clear increase of the ground motion and a related disturbance of the seismic recordings. The station threshold for signal detection below 2 Hz is reduced after the installation of a new wind farm in the area around Landau. This effect occurs even up to distances to the WTs of more than 5 kilometers. The increasing noise level depends also clearly on wind speed, which indicate also the WT origin related with the signals. Using short-term measurements during few hours, we are able to determine the maximum of the PSD values for different discrete frequencies as function of distance to the next WT and to fit a power-law decay curve proportional to 1/rb to the data. In this way we can differentiate between near- and far-field effects of the seismic wave propagation of WTs. A clear frequency dependent decay can be observed, for which high frequencies are more attenuated than lower frequencies, probably due to scattering processes. The new results will help for a better understanding of WTs as a seismic noise source and their interaction with nearby seismic stations and other infrastructure. Seismic data were provided by "Erdbebendienst Südwest", "Federal Institute for Geosciences and
Distributed Model Predictive Control for Active Power Control of Wind Farm
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard
2014-01-01
This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....
International Nuclear Information System (INIS)
Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami
2017-01-01
Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.
On Practical tuning of Model Uncertainty in Wind Turbine Model Predictive Control
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Hovgaard, Tobias
2015-01-01
Model predictive control (MPC) has in previous works been applied on wind turbines with promising results. These results apply linear MPC, i.e., linear models linearized at different operational points depending on the wind speed. The linearized models are derived from a nonlinear first principles...... model of a wind turbine. In this paper, we investigate the impact of this approach on the performance of a wind turbine. In particular, we focus on the most non-linear operational ranges of a wind turbine. The MPC controller is designed for, tested, and evaluated at an industrial high fidelity wind...
Energy Technology Data Exchange (ETDEWEB)
Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)
2009-07-01
In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)
Predicting wind shear effects: A study of Minnesota wind data collected at heights up to 70 meters
Energy Technology Data Exchange (ETDEWEB)
Artig, R. [Minnesota Dept. of Public Service, St. Paul, MN (United States)
1997-12-31
The Minnesota Department of Public Service (DPS) collects wind data at carefully selected sites around the state and analyzes the data to determine Minnesota`s wind power potential. DPS recently installed advanced new monitoring equipment at these sites and began to collect wind data at 30, 50, and 70 meters above ground level, with two anemometers at each level. Previously, the Department had not collected data at heights above ground level higher than 30 meters. DPS also, with the U.S. Department of Energy (DOE), installed four sophisticated monitoring sites as part of a Tall Tower Wind Shear Study that is assessing the effects of wind shear on wind power potential. At these sites, wind data are being collected at the 10, 30, 40, 50, 60, and 70 meter heights. This paper presents the preliminary results of the analysis of wind data from all sites. These preliminary results indicate that the traditional 1/7 power law does not effectively predict wind shear in Minnesota, and the result is an underestimation of Minnesota`s wind power potential at higher heights. Using a power factor of 1/5 or 1/4 may be more accurate and provide sound justification for installing wind turbines on taller towers in Minnesota.
A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
International Nuclear Information System (INIS)
Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.
2011-01-01
The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.
Dual-loop control strategy for DFIG-based Wind turbines under grid voltage disturbances
DEFF Research Database (Denmark)
Zhu, Rongwu; Chen, Zhe; Tang, Yi
2016-01-01
, but also decay the stator transient flux, and avoid the accumulation of the stator transient flux. Moreover, the proposed strategy can obtain nearly constant stator active power and electromagnetic torque, which may prolong the lifetime of the drive train. A case study on a typical 2-MW DFIG-based wind......For a multimegawatts doubly-fed induction generator (DFIG), the grid voltage disturbances may affect the stator flux and induce the transient stator flux, due to the direct connection of the stator and the grid. The accumulation of the transient stator flux caused by the variations of the stator...... turbine demonstrating the effectiveness of the proposed control methods is verified with simulations in MATLAB/Simulink. The proposed control methods are also experimentally validated using a scaled-down 7.5-kW DFIG. The simulation and experimental results clearly validate the effectiveness...
Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms
DEFF Research Database (Denmark)
Asgarpour, Masoud; Sørensen, John Dalsgaard
2018-01-01
The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...... monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution...
Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms
DEFF Research Database (Denmark)
Asgarpour, Masoud; Sørensen, John Dalsgaard
2018-01-01
monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...
Dst Prediction Based on Solar Wind Parameters
Directory of Open Access Journals (Sweden)
Yoon-Kyung Park
2009-12-01
Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.
Coordinated Voltage Control of a Wind Farm based on Model Predictive Control
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai
2016-01-01
This paper presents an autonomous wind farm voltage controller based on Model Predictive Control (MPC). The reactive power compensation and voltage regulation devices of the wind farm include Static Var Compensators (SVCs), Static Var Generators (SVGs), Wind Turbine Generators (WTGs) and On...... are calculated based on an analytical method to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both voltage violated and normal operation conditions. A wind farm with 20 wind turbines was used to conduct case studies to verify the proposed coordinated...
Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability
DEFF Research Database (Denmark)
Koukoura, Christina
To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...
International Nuclear Information System (INIS)
2008-01-01
Wind turbines and the movement of their blades can have penalizing effects on the processing of radars data. These disturbances can have a strong impact on the air, maritime and fluvial safety, on the protection of the territory and on the prevention of natural hazards. Reports made by the national agency of frequencies (ANFR) have established recommendations for the definition of protection areas (5 km) and coordination areas (5 to 30 km) which have to be taken into consideration prior to any project of wind turbine. (J.S.)
International Nuclear Information System (INIS)
Trussoni, E.; Ferrari, A.; Rosner, R.; Tsinganos, K.
1988-01-01
The temporal evolution of disturbances in a spherically symmetric polytropic wind from a central object is studied. Such disturbances may be due to localized momentum addition/subtraction, as, for example, by MHD waves, heating/cooling mechanisms in the outflow, or localized deviations from spherical symmetric expansion. The evolution of an initial perturbed state to a continuous or discontinuous final equilibrium state, as predicted by previous analytic calculations for stationary flows, is followed. It is shown that some of the predicted discontinuous equilibrium states are not physically accessible, while the attainment of the remaining equilibrium states depends on both the temporal and the spatial parameters characterizing the perturbation. The results are derived for solar conditions, but in fact can be applied to outflows in other astrophysical systems. In particular, applications to the solar wind and flows in astrophysical jets are discussed. 32 references
Hernandez, A. J.
2015-12-01
The Landsat archive is increasingly being used to detect trends in the occurrence of forest disturbance. Beyond information about the amount of area affected, forest managers need to know if and how disturbance regimes change. The National Forest System (NFS) has developed a comprehensive plan for carbon monitoring that requires a detailed temporal mapping of forest disturbances across 75 million hectares. A long-term annual time series that shows the timing, extent, and type of disturbance beginning in 1990 and ending in 2011 has been prepared for several USFS Regions, including the Northern Region. Our mapping starts with an automated detection of annual disturbances using a time series of historical Landsat imagery. Automated detections are meticulously inspected, corrected and labeled using various USFS ancillary datasets. The resulting maps of verified disturbance show the timing and types are fires, harvests, insect activity, disease, and abiotic (wind, drought, avalanche) damage. Also, the magnitude of each change event is modeled in terms of the proportion of canopy cover lost. The sequence of disturbances for every pixel since 1990 has been consistently mapped and is available across the entirety of NFS. Our datasets contain sufficient information to describe the frequency of stand replacement, as well as how often disturbance results in only a partial loss of canopy. This information provides empirical insight into how an initial disturbance may predispose a stand to further disturbance, and it also show a climatic signal in the occurrence of processes such as fire and insect epidemics. Thus, we have the information to model the likelihood of occurrence of certain disturbances after a given event (i.e. if we have a fire in the past what does that do to the likelihood of occurrence of insects in the future). Here, we explore if previous disturbance history is a reliable predictor of additional disturbance in the future and we present results of applying
A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal
Energy Technology Data Exchange (ETDEWEB)
Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)
2011-01-15
The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)
International Nuclear Information System (INIS)
Chen, Kuilin; Yu, Jie
2014-01-01
Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations
Simulation of wake effects between two wind farms
International Nuclear Information System (INIS)
Hansen, K S; Réthoré, P-E; Peña, A; Ott, S; Van der Laan, M P; Volker, P; Palma, J; Hevia, B G; Prospathopoulos, J; Schepers, G; Palomares, A
2015-01-01
SCADA data, recorded on the downstream wind farm, has been used to identify flow cases with visible clustering effects. The inflow condition is derived from a partly undisturbed wind turbine, due to lack of mast measurements. The SCADA data analysis concludes that centre of the deficit for the downstream wind farm with disturbed inflow has a distinct visible maximum deficit zone located only 5-10D downstream from the entrance. This zone, representing 20-30% speed reduction, increases and moves downstream for increasing cluster effect and is not visible outside a flow sector of 20-30°. The eight flow models represented in this benchmark include both RANS models, mesoscale models and engineering models. The flow cases, identified according to the wind speed level and inflow sector, have been simulated and validated with the SCADA results. The model validation concludes that all models more or less are able to predict the location and size of the deficit zone inside the downwind wind farm. (paper)
Predicting the cumulative effect of multiple disturbances on seagrass connectivity.
Grech, Alana; Hanert, Emmanuel; McKenzie, Len; Rasheed, Michael; Thomas, Christopher; Tol, Samantha; Wang, Mingzhu; Waycott, Michelle; Wolter, Jolan; Coles, Rob
2018-03-15
The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non-foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average >245 km, about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules; therefore, management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful. © 2018 John Wiley & Sons Ltd.
Disturbance estimator based predictive current control of grid-connected inverters
Al-Khafaji, Ahmed Samawi Ghthwan
2013-01-01
ABSTRACT: The work presented in my thesis considers one of the modern discrete-time control approaches based on digital signal processing methods, that have been developed to improve the performance control of grid-connected three-phase inverters. Disturbance estimator based predictive current control of grid-connected inverters is proposed. For inverter modeling with respect to the design of current controllers, we choose the d-q synchronous reference frame to make it easier to understand an...
A hybrid measure-correlate-predict method for long-term wind condition assessment
International Nuclear Information System (INIS)
Zhang, Jie; Chowdhury, Souma; Messac, Achille; Hodge, Bri-Mathias
2014-01-01
Highlights: • A hybrid measure-correlate-predict (MCP) methodology with greater accuracy is developed. • Three sets of performance metrics are proposed to evaluate the hybrid MCP method. • Both wind speed and direction are considered in the hybrid MCP method. • The best combination of MCP algorithms is determined. • The developed hybrid MCP method is uniquely helpful for long-term wind resource assessment. - Abstract: This paper develops a hybrid measure-correlate-predict (MCP) strategy to assess long-term wind resource variations at a farm site. The hybrid MCP method uses recorded data from multiple reference stations to estimate long-term wind conditions at a target wind plant site with greater accuracy than is possible with data from a single reference station. The weight of each reference station in the hybrid strategy is determined by the (i) distance and (ii) elevation differences between the target farm site and each reference station. In this case, the wind data is divided into sectors according to the wind direction, and the MCP strategy is implemented for each wind direction sector separately. The applicability of the proposed hybrid strategy is investigated using five MCP methods: (i) the linear regression; (ii) the variance ratio; (iii) the Weibull scale; (iv) the artificial neural networks; and (v) the support vector regression. To implement the hybrid MCP methodology, we use hourly averaged wind data recorded at five stations in the state of Minnesota between 07-01-1996 and 06-30-2004. Three sets of performance metrics are used to evaluate the hybrid MCP method. The first set of metrics analyze the statistical performance, including the mean wind speed, wind speed variance, root mean square error, and mean absolute error. The second set of metrics evaluate the distribution of long-term wind speed; to this end, the Weibull distribution and the Multivariate and Multimodal Wind Distribution models are adopted. The third set of metrics analyze
Wind gust estimation by combining numerical weather prediction model and statistical post-processing
Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George
2017-04-01
The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.
Wind power application research on the fusion of the determination and ensemble prediction
Lan, Shi; Lina, Xu; Yuzhu, Hao
2017-07-01
The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.
International Nuclear Information System (INIS)
Abdu, M.A.; Sobral, J.H.A.; Trivedi, N.B.; Reddy, B.M.; Fejer, B.G.; Szuszczewicz, E.P.; Walker, G.O.; Kikuchi, T.
1990-01-01
Developments of equatorial Ionization Anomaly (EIA) under quiescent and disturbed ionospheric conditions are investigated using the data collected from the low-latitude network of ionosondes and magnetometers operated at different longitude sectors of the globe as a part of the SUNDIAL 86 campaign (22 September to 3 October, 1986). Based on case studies of EIA developments, attention is focused on identifiying the EIA response to changes in the electric fields associated with the equatorial electrojet and counter electrojet events. The response time of the EIA to electric field changes is found to vary from 2.5 to 4 h. An anomalous EIA development observed in the morning sector on September 23 suggested possible electric field penetration to low latitude during a substorm energy storage/Dst development phase. The analysis also shows that the afternoon EIA could be inhibited due to equatorward blowing disturbed neutral winds. The results of the present analysis emphasize the need for pursuing further investigations for the response of EIA to magnetosphere-induced disturbances
DEFF Research Database (Denmark)
Christiansen, Søren; Tabatabaeipour, Seyed Mojtaba; Bak, Thomas
2013-01-01
pitch such that the state trajectories of the controlled system tracks the reference trajectories. The framework is demonstrated with a reference model of the desired closed-loop system undisturbed by the incident waves. This allows the wave-induced motion of the platform to be damped significantly...... compared to a baseline floating wind turbine controller at the cost of more pitch action....
Analysis of chaos in high-dimensional wind power system.
Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping
2018-01-01
A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.
Directory of Open Access Journals (Sweden)
Douglas Halamay
2014-09-01
Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.
International Nuclear Information System (INIS)
Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.
2013-01-01
Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability
The effects of tropical wind data on the prediction of ultralong waves
Baker, W. E.
1981-01-01
The influence of tropical wind data on the prediction of planetary waves were studied. Two assimilation experiments were performed, one with and one without FGGE tropical winds. The planetary wave error was then analyzed in 72 h forecasts from the initial conditions provided by the two assimilations.
Fan, Fang; Zhou, Ya; Liu, Xianchen
2017-07-01
To examine the cross-sectional and longitudinal associations between sleep disturbance and posttraumatic stress disorder (PTSD) and depressive symptoms in a large cohort of adolescents exposed to the 2008 Wenchuan earthquake in China. Participants were 1,573 adolescents (mean age at initial survey = 15.0 years, SD = 1.3 years; 46% male) in the Wenchuan Earthquake Adolescent Health Cohort (WEAHC) in Dujiangyan, China, 20 km away from the east epicenter. The Pittsburgh Sleep Quality Index, Post-Traumatic Stress Disorder Self-Rating Scale, and Depression Self-Rating Scale for Children were used to assess participants' sleep, PTSD symptoms, and depressive symptoms, respectively, at 12 months (T12m) and 24 months (T24m) after the Wenchuan earthquake that occurred on May 12, 2008. At T12m and T24m, 38.3% and 37.5% of participants reported sleep disturbance, 22.5% and 14.0% reported PTSD symptoms, and 41.0% and 38.3% reported depressive symptoms, respectively. The prevalence rates of PTSD and depressive symptoms at T12m and T24m significantly increased with sleep disturbance and short sleep duration. After adjusting for demographics, earthquake exposure, and PTSD/depressive symptoms at T12m, sleep disturbance at T12m was significantly associated with increased risk for PTSD (odds ratio [OR] = 1.80; 95% CI, 1.17-2.75) and depressive symptoms (OR = 1.51; 95% CI, 1.14-2.02) at T24m. Furthermore, sleep disturbance predicted the persistence of PTSD (OR = 2.35; 95% CI, 1.43-3.85) and depressive symptoms (OR = 2.41; 95% CI, 1.80-3.24). Sleep disturbance, PTSD, and depressive symptoms were prevalent and persistent in adolescents at 12 and 24 months after exposure to the Wenchuan earthquake. Sleep disturbance predicts the development and persistence of PTSD and depressive symptoms. Early assessment and treatment of sleep disturbance may be an important strategy for prevention and intervention of PTSD and depression in adolescent trauma survivors. © Copyright 2017 Physicians
International Nuclear Information System (INIS)
Prospathopoulos, John M.; Voutsinas, Spyros G.
2006-01-01
Various propagation models have been developed to estimate the level of noise near residential areas. Predictions and measurements have proven that proper modelling of the propagation medium is of particular importance. In the present work, calculations are performed using a ray theory methodology. The ray trajectory and transport equations are derived from the linear acoustics equations for a moving medium in three dimensions. Ground and atmospheric absorption, wave refraction and diffraction and atmospheric turbulence are taken into account by introducing appropriate coefficients in the equations. In the case of a wind turbine (W/T) it is assumed that noise is produced by a point source located at the rotor centre. Given the sound power spectrum, the noise spectrum at the receiver is obtained by solving the axisymmetric propagation problem. The procedure consists of (a) finding the eigenrays, (b) calculating the energy losses along the eigenrays and (c) synthesizing the sound pressure level (SPL) by superposing the contributions of the eigenrays. In the case of a wind park the total SPL is calculated by superposing the contributions of all W/Ts. Application is made to five cases of isolated W/Ts in terrains of varying complexity. In flat or even smooth terrain the predictions agree well with the measurements. In complex terrain the predictions can be considered satisfactory, taking into account the assumption of constant wind velocity profile. Application to a wind park shows clearly the influence of the terrain on the wind velocity and consequently on the SPL. (Author)
A Gaussian process regression based hybrid approach for short-term wind speed prediction
International Nuclear Information System (INIS)
Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian
2016-01-01
Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.
Energy Technology Data Exchange (ETDEWEB)
Khan, D. [Entec UK Ltd., Doherty Innovation Centre, Penicuik (United Kingdom); Infield, D. [Loughborough Univ., Centre for Renewable Energy Systems Tecnology, Loughborough (United Kingdom)
2002-03-01
The rise and fall of the sea surface due to tides effectively moves an offshore wind turbine hub through the wind shear profile. This effect is quantified using measured data from 3 offshore UK sites. Statistical evidence of the influence of tide on mean wind speed and turbulence is presented. The implications of this effect for predicting offshore wind resource are outlined. (au)
Preconditioning of Interplanetary Space Due to Transient CME Disturbances
International Nuclear Information System (INIS)
Temmer, M.; Reiss, M. A.; Hofmeister, S. J.; Veronig, A. M.; Nikolic, L.
2017-01-01
Interplanetary space is characteristically structured mainly by high-speed solar wind streams emanating from coronal holes and transient disturbances such as coronal mass ejections (CMEs). While high-speed solar wind streams pose a continuous outflow, CMEs abruptly disrupt the rather steady structure, causing large deviations from the quiet solar wind conditions. For the first time, we give a quantification of the duration of disturbed conditions (preconditioning) for interplanetary space caused by CMEs. To this aim, we investigate the plasma speed component of the solar wind and the impact of in situ detected interplanetary CMEs (ICMEs), compared to different background solar wind models (ESWF, WSA, persistence model) for the time range 2011–2015. We quantify in terms of standard error measures the deviations between modeled background solar wind speed and observed solar wind speed. Using the mean absolute error, we obtain an average deviation for quiet solar activity within a range of 75.1–83.1 km s −1 . Compared to this baseline level, periods within the ICME interval showed an increase of 18%–32% above the expected background, and the period of two days after the ICME displayed an increase of 9%–24%. We obtain a total duration of enhanced deviations over about three and up to six days after the ICME start, which is much longer than the average duration of an ICME disturbance itself (∼1.3 days), concluding that interplanetary space needs ∼2–5 days to recover from the impact of ICMEs. The obtained results have strong implications for studying CME propagation behavior and also for space weather forecasting.
Preconditioning of Interplanetary Space Due to Transient CME Disturbances
Energy Technology Data Exchange (ETDEWEB)
Temmer, M.; Reiss, M. A.; Hofmeister, S. J.; Veronig, A. M. [Institute of Physics, University of Graz, Universitätsplatz 5/II, A-8010 Graz (Austria); Nikolic, L., E-mail: manuela.temmer@uni-graz.at [Canadian Hazards Information Service, Natural Resources Canada, 2617 Anderson Road, Ottawa, Ontario K1A 0Y3 (Canada)
2017-02-01
Interplanetary space is characteristically structured mainly by high-speed solar wind streams emanating from coronal holes and transient disturbances such as coronal mass ejections (CMEs). While high-speed solar wind streams pose a continuous outflow, CMEs abruptly disrupt the rather steady structure, causing large deviations from the quiet solar wind conditions. For the first time, we give a quantification of the duration of disturbed conditions (preconditioning) for interplanetary space caused by CMEs. To this aim, we investigate the plasma speed component of the solar wind and the impact of in situ detected interplanetary CMEs (ICMEs), compared to different background solar wind models (ESWF, WSA, persistence model) for the time range 2011–2015. We quantify in terms of standard error measures the deviations between modeled background solar wind speed and observed solar wind speed. Using the mean absolute error, we obtain an average deviation for quiet solar activity within a range of 75.1–83.1 km s{sup −1}. Compared to this baseline level, periods within the ICME interval showed an increase of 18%–32% above the expected background, and the period of two days after the ICME displayed an increase of 9%–24%. We obtain a total duration of enhanced deviations over about three and up to six days after the ICME start, which is much longer than the average duration of an ICME disturbance itself (∼1.3 days), concluding that interplanetary space needs ∼2–5 days to recover from the impact of ICMEs. The obtained results have strong implications for studying CME propagation behavior and also for space weather forecasting.
Progress in wind tunnel experimental techniques for wind turbine?
Institute of Scientific and Technical Information of China (English)
Jingping XIAO; Li CHEN; Qiang WANG; Qiao WANG
2016-01-01
Based on the unsteady aerodynamics experiment (UAE) phase VI and the model experiment in controlled conditions (MEXICO) projects and the related research carried out in China Aerodynamic Research and Development Center (CARDC), the recent progress in the wind tunnel experimental techniques for the wind turbine is sum-marized. Measurement techniques commonly used for di?erent types of wind tunnel ex-periments for wind turbine are reviewed. Important research achievements are discussed, such as the wind tunnel disturbance, the equivalence of the airfoil in?ow condition, the three-dimensional (3D) e?ect, the dynamic in?ow in?uence, the ?ow ?eld structure, and the vortex induction. The corresponding research at CARDC and some ideas on the large wind turbine are also introduced.
International Nuclear Information System (INIS)
Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Saboohi, Hadi; Abdul Wahab, Ainuddin Wahid; Protić, Milan; Zalnezhad, Erfan; Mirhashemi, Seyed Mohammad Amin
2014-01-01
Highlights: • Probabilistic distribution functions of wind speed. • Two parameter Weibull probability distribution. • To build an effective prediction model of distribution of wind speed. • Support vector regression application as probability function for wind speed. - Abstract: The probabilistic distribution of wind speed is among the more significant wind characteristics in examining wind energy potential and the performance of wind energy conversion systems. When the wind speed probability distribution is known, the wind energy distribution can be easily obtained. Therefore, the probability distribution of wind speed is a very important piece of information required in assessing wind energy potential. For this reason, a large number of studies have been established concerning the use of a variety of probability density functions to describe wind speed frequency distributions. Although the two-parameter Weibull distribution comprises a widely used and accepted method, solving the function is very challenging. In this study, the polynomial and radial basis functions (RBF) are applied as the kernel function of support vector regression (SVR) to estimate two parameters of the Weibull distribution function according to previously established analytical methods. Rather than minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound, so as to achieve generalized performance. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies
Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation
Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi
2016-09-01
We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.
Gerwing, Travis G.; Allen Gerwing, Alyssa M.; Macdonald, Tara; Cox, Kieran; Juanes, Francis; Dudas, Sarah E.
2017-11-01
The Intermediate Disturbance Hypothesis (IDH) predicts that disturbances of an intermediate frequency or intensity will maximize community biodiversity/richness. Once almost universally accepted, controversy now surrounds this hypothesis, and there have even been calls for its abandonment. Therefore, we experimentally evaluated if an infaunal community along the north coast of British Columbia, Canada, would respond to disturbances as predicted by the IDH. The characteristics of this soft-sediment intertidal mudflat (productivity, species pool, population growth rate) maximized our chances of finding evidence to support the IDH. More specifically, we tested if intermediate severities and frequencies of disturbance maximized infaunal community richness by mechanically disturbing sediment, and varying the intensity (0%, 25%, 50%, 75%, and 100% of the surface area of a plot disturbed) and frequency of sediment disturbance (never, once, twice, and every week during a four week period). No effect of frequency or intensity of sediment disturbance on community richness was observed. Further, none of our experimental treatments were statistically different than the controls. This is likely due to the subtle difference between successional stages in this soft-sediment habitat (difference of less than one taxa between treatments). Therefore, in habitats whose productivity, regional species pool, and population growth rates would otherwise suggest a response to disturbances as predicted by the IDH, minor differences between successional stages may result in richness patterns that deviate from those predicted by the IDH.
Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions
International Nuclear Information System (INIS)
Liu, Hui; Tian, Hong-qi; Li, Yan-fei; Zhang, Lei
2015-01-01
Highlights: • Four hybrid algorithms are proposed for the wind speed decomposition. • Adaboost algorithm is adopted to provide a hybrid training framework. • MLP neural networks are built to do the forecasting computation. • Four important network training algorithms are included in the MLP networks. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. In this paper, four different hybrid methods are proposed for the high-precision multi-step wind speed predictions based on the Adaboost (Adaptive Boosting) algorithm and the MLP (Multilayer Perceptron) neural networks. In the hybrid Adaboost–MLP forecasting architecture, four important algorithms are adopted for the training and modeling of the MLP neural networks, including GD-ALR-BP algorithm, GDM-ALR-BP algorithm, CG-BP-FR algorithm and BFGS algorithm. The aim of the study is to investigate the promoted forecasting percentages of the MLP neural networks by the Adaboost algorithm’ optimization under various training algorithms. The hybrid models in the performance comparison include Adaboost–GD-ALR-BP–MLP, Adaboost–GDM-ALR-BP–MLP, Adaboost–CG-BP-FR–MLP, Adaboost–BFGS–MLP, GD-ALR-BP–MLP, GDM-ALR-BP–MLP, CG-BP-FR–MLP and BFGS–MLP. Two experimental results show that: (1) the proposed hybrid Adaboost–MLP forecasting architecture is effective for the wind speed predictions; (2) the Adaboost algorithm has promoted the forecasting performance of the MLP neural networks considerably; (3) among the proposed Adaboost–MLP forecasting models, the Adaboost–CG-BP-FR–MLP model has the best performance; and (4) the improved percentages of the MLP neural networks by the Adaboost algorithm decrease step by step with the following sequence of training algorithms as: GD-ALR-BP, GDM-ALR-BP, CG-BP-FR and BFGS
DEFF Research Database (Denmark)
Tatrallyay, M.; Erdos, G.; Nemeth, Z.
2012-01-01
by the Cluster spacecraft were best predicted by the 3-D model of Lin et al. (2010). The applied empirical bow shock models and the 3-D semi-empiric bow shock model combined with magnetohydrodynamic (MHD) solution proved to be insufficient for predicting the observed unusual bow shock locations during large...... interplanetary disturbances. The results of a global 3-D MHD model were in good agreement with the Cluster observations on 17 January 2005, but they did not predict the bow shock crossings on 31 October 2003....... of three magnetopause and four bow shock models which describe them in considerably different ways using statistical methods based on observations. A new 2-D magnetopause model is introduced (based on Verigin et al., 2009) which takes into account the pressure of the compressed magnetosheath field raised...
Walz, M. A.; Donat, M.; Leckebusch, G. C.
2017-12-01
As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.
Performance and wake predictions of HAWTs in wind farms
Energy Technology Data Exchange (ETDEWEB)
Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)
1997-12-31
The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.
Wind resource estimation and siting of wind turbines
DEFF Research Database (Denmark)
Lundtang Petersen, Erik; Mortensen, N.G.; Landberg, L.
1994-01-01
Detailed knowledge of the characteristics of the natural wind is necessary for the design, planning and operational aspect of wind energy systems. Here, we shall only be concerned with those meteorological aspects of wind energy planning that are termed wind resource estimation. The estimation...... of the wind resource ranges from the overall estimation of the mean energy content of the wind over a large area - called regional assessment - to the prediction of the average yearly energy production of a specific wind turbine at a specific location - called siting. A regional assessment will most often...... lead to a so-called wind atlas. A precise prediction of the wind speed at a given site is essential because for aerodynamic reasons the power output of a wind turbine is proportional to the third power of the wind speed, hence even small errors in prediction of wind speed may result in large deviations...
Forecasting Electricity Spot Prices Accounting for Wind Power Predictions
DEFF Research Database (Denmark)
Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg
2013-01-01
A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...
Simulation for Grid Connected Wind Turbines with Fluctuating
Ye, Ying; Fu, Yang; Wei, Shurong
This paper establishes the whole dynamic model of wind turbine generator system which contains the wind speed model and DFIG wind turbines model .A simulation sample based on the mathematical models is built by using MATLAB in this paper. Research are did on the performance characteristics of doubly-fed wind generators (DFIG) which connected to power grid with three-phase ground fault and the disturbance by gust and mixed wind. The capacity of the wind farm is 9MW which consists of doubly-fed wind generators (DFIG). Simulation results demonstrate that the three-phase ground fault occurs on grid side runs less affected on the stability of doubly-fed wind generators. However, as a power source, fluctuations of the wind speed will run a large impact on stability of double-fed wind generators. The results also show that if the two disturbances occur in the meantime, the situation will be very serious.
Model predictive control of a wind turbine modelled in Simpack
International Nuclear Information System (INIS)
Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G
2014-01-01
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine
Model predictive control of a wind turbine modelled in Simpack
Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.
2014-06-01
Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to
Directory of Open Access Journals (Sweden)
Deockho Kim
2017-05-01
Full Text Available Due to the intermittency of wind power generation, it is very hard to manage its system operation and planning. In order to incorporate higher wind power penetrations into power systems that maintain secure and economic power system operation, an accurate and efficient estimation of wind power outputs is needed. In this paper, we propose the stochastic prediction of wind generating resources using an enhanced ensemble model for Jeju Island’s wind farms in South Korea. When selecting the potential sites of wind farms, wind speed data at points of interest are not always available. We apply the Kriging method, which is one of spatial interpolation, to estimate wind speed at potential sites. We also consider a wind profile power law to correct wind speed along the turbine height and terrain characteristics. After that, we used estimated wind speed data to calculate wind power output and select the best wind farm sites using a Weibull distribution. Probability density function (PDF or cumulative density function (CDF is used to estimate the probability of wind speed. The wind speed data is classified along the manufacturer’s power curve data. Therefore, the probability of wind speed is also given in accordance with classified values. The average wind power output is estimated in the form of a confidence interval. The empirical data of meteorological towers from Jeju Island in Korea is used to interpolate the wind speed data spatially at potential sites. Finally, we propose the best wind farm site among the four potential wind farm sites.
Yao, Zhigang; Xue, Zuo; He, Ruoying; Bao, Xianwen; Song, Jun
2016-08-01
A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexico (GOM), and the Caribbean Sea. The statistical relationship is built upon linear regressions between the empirical orthogonal function (EOF) spaces of a cross- calibrated, multi-platform, multi-instrument ocean surface wind velocity dataset (predictand) and the global NCEP wind reanalysis (predictor) over a 10 year period from 2000 to 2009. The statistical relationship is validated before applications and its effectiveness is confirmed by the good agreement between downscaled wind fields based on the NCEP reanalysis and in-situ surface wind measured at 16 National Data Buoy Center (NDBC) buoys in the U.S. east coastal ocean and the GOM during 1992-1999. The predictand-predictor relationship is applied to IPCC GFDL model output (2.0°×2.5°) of downscaled coastal wind at 0.25°×0.25° resolution. The temporal and spatial variability of future predicted wind speeds and wind energy potential over the study region are further quantified. It is shown that wind speed and power would significantly be reduced in the high CO2 climate scenario offshore of the mid-Atlantic and northeast U.S., with the speed falling to one quarter of its original value.
Wind gust models derived from field data
Gawronski, W.
1995-01-01
Wind data measured during a field experiment were used to verify the analytical model of wind gusts. Good coincidence was observed; the only discrepancy occurred for the azimuth error in the front and back winds, where the simulated errors were smaller than the measured ones. This happened because of the assumption of the spatial coherence of the wind gust model, which generated a symmetric antenna load and, in consequence, a low azimuth servo error. This result indicates a need for upgrading the wind gust model to a spatially incoherent one that will reflect the real gusts in a more accurate manner. In order to design a controller with wind disturbance rejection properties, the wind disturbance should be known at the input to the antenna rate loop model. The second task, therefore, consists of developing a digital filter that simulates the wind gusts at the antenna rate input. This filter matches the spectrum of the measured servo errors. In this scenario, the wind gusts are generated by introducing white noise to the filter input.
Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data
DEFF Research Database (Denmark)
Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard
2014-01-01
The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...... that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade....
Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm
Directory of Open Access Journals (Sweden)
Qunli Wu
2015-12-01
Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.
Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control
DEFF Research Database (Denmark)
Guo, Yifei; Gao, Houlei; Wu, Qiuwei
2018-01-01
This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...
DEFF Research Database (Denmark)
Pinson, Pierre; Tastu, Julija
2014-01-01
A new score for the evaluation of interval forecasts, the so-called coverage width-based criterion (CWC), was proposed and utilized.. This score has been used for the tuning (in-sample) and genuine evaluation (out-ofsample) of prediction intervals for various applications, e.g., electric load [1......], electricity prices [2], general purpose prediction [3], and wind power generation [4], [5]. Indeed, two papers by the same authors appearing in the IEEE Transactions On Sustainable Energy employ that score and use it to conclude on the comparative quality of alternative approaches to interval forecasting...
Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri
2017-01-01
In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here
Statistical Maps of Ground Magnetic Disturbance Derived from Global Geospace Models
Rigler, E. J.; Wiltberger, M. J.; Love, J. J.
2017-12-01
Electric currents in space are the principal driver of magnetic variations measured at Earth's surface. These in turn induce geoelectric fields that present a natural hazard for technological systems like high-voltage power distribution networks. Modern global geospace models can reasonably simulate large-scale geomagnetic response to solar wind variations, but they are less successful at deterministic predictions of intense localized geomagnetic activity that most impacts technological systems on the ground. Still, recent studies have shown that these models can accurately reproduce the spatial statistical distributions of geomagnetic activity, suggesting that their physics are largely correct. Since the magnetosphere is a largely externally driven system, most model-measurement discrepancies probably arise from uncertain boundary conditions. So, with realistic distributions of solar wind parameters to establish its boundary conditions, we use the Lyon-Fedder-Mobarry (LFM) geospace model to build a synthetic multivariate statistical model of gridded ground magnetic disturbance. From this, we analyze the spatial modes of geomagnetic response, regress on available measurements to fill in unsampled locations on the grid, and estimate the global probability distribution of extreme magnetic disturbance. The latter offers a prototype geomagnetic "hazard map", similar to those used to characterize better-known geophysical hazards like earthquakes and floods.
Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction
Directory of Open Access Journals (Sweden)
Changbin Hu
2015-02-01
Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.
Directory of Open Access Journals (Sweden)
Monika Budzáková
2013-03-01
Full Text Available A strong windstorm in November 2004 resulted in a huge blown-down spruce forest area in the southern part of the Tatra National Park in the Western Carpathians in Slovakia, Central Europe. The aim of this work is to study the vegetation composition of spruce forest at differently managed sites four years after this disturbance. Four study areas were selected for this purpose: (i an area where the fallen trees were extracted and new seedlings were planted; (ii an area, which was hit by a forest fire after the extraction; (iii an area where no active management was applied; (iv a reference forest unaffected by such disturbance. A total of 100 plots were selected, 25 of each area type. The result of DCA and CCA analyses consistently indicated that after this short period the non-extracted and extracted areas are currently most similar to the reference forest area, while the fire affected area differed. A one-way ANOVA comparing species cover for the different plot sizes indicated some significant differences between the extracted and non-extracted plots. The abundance of certain species commonly occurring in spruce forests, such as Dyopteris carthusiana agg., Vaccinium myrtillus and Avenella flexuosa, correlated weli with the non-extracted plots, compared to the extracted plots. Coverage of these species was lowest on burned plots. The lowest Shannon-Wiener’s diversity values were recorded in burned plots. This was most likely a consequence of mono-dominant competitive species spread, (mainly Chamerion angustifolium which profited from the altered ecological conditions following the fire. Although some differences were also registered in the Shannon-Wiener diversity index between the remaining research plots, however these were not statistically significant. The most important results of our investigations include the extensive influence of fire disturbance on vegetation. Study revealed that the wind-disturbed area is able to regenerate
Ionospheric disturbance dynamo
International Nuclear Information System (INIS)
Blanc, M.; Richmond, A.D.
1980-01-01
A numerical simulation study of the thermospheric winds produced by auroral heating during magnetic storms, and of their global dynamo effects, establishes the main features of the ionospheric disturbanc dynamo. Driven by auroral heating, a Hadley cell is created with equatorward winds blowing above about 120 km at mid-latitudes. The transport of angular momentum by these winds produces a subrotation of the midlatitude thermosphere, or westward motion with respect to the earth. The westward winds in turn drive equatorward Pedersen currents which accumulate charge toward the equator, resulting in the generation of a poleward electric field, a westward E x B drift, and an eastward current. When realistic local time conductivity variations are simulated, the eastward mid-latitude current is found to close partly via lower latitudes, resulting in an 'anti-Sq' type of current vortex. Both electric field and current at low latitudes thus vary in opposition to their normal quiet-day behavior. This total pattern of distrubance winds, electric fields, and currents is superimposed upon the background quiet-day pattern. When the neutral winds are artificially confined on the nightside, the basic pattern of predominantly westward E x B plasma drifts still prevails on the nightside but no longer extends into the dayside. Considerable observational evidence exists, suggesting that the ionospheric disturbance dynamo has an appreciable influence on storm-time ionospheric electric fields at middle and low latitudes
Equivalent models of wind farms by using aggregated wind turbines and equivalent winds
International Nuclear Information System (INIS)
Fernandez, L.M.; Garcia, C.A.; Saenz, J.R.; Jurado, F.
2009-01-01
As a result of the increasing wind farms penetration on power systems, the wind farms begin to influence power system, and therefore the modeling of wind farms has become an interesting research topic. In this paper, new equivalent models of wind farms equipped with wind turbines based on squirrel-cage induction generators and doubly-fed induction generators are proposed to represent the collective behavior on large power systems simulations, instead of using a complete model of wind farms where all the wind turbines are modeled. The models proposed here are based on aggregating wind turbines into an equivalent wind turbine which receives an equivalent wind of the ones incident on the aggregated wind turbines. The equivalent wind turbine presents re-scaled power capacity and the same complete model as the individual wind turbines, which supposes the main feature of the present equivalent models. Two equivalent winds are evaluated in this work: (1) the average wind from the ones incident on the aggregated wind turbines with similar winds, and (2) an equivalent incoming wind derived from the power curve and the wind incident on each wind turbine. The effectiveness of the equivalent models to represent the collective response of the wind farm at the point of common coupling to grid is demonstrated by comparison with the wind farm response obtained from the detailed model during power system dynamic simulations, such as wind fluctuations and a grid disturbance. The present models can be used for grid integration studies of large power system with an important reduction of the model order and the computation time
Directory of Open Access Journals (Sweden)
Elvira Mächler
Full Text Available Factors such as increased mobility of humans, global trade and climate change are affecting the range of many species, and cause large-scale translocations of species beyond their native range. Many introduced species have a strong negative influence on the new local environment and lead to high economic costs. There is a strong interest to understand why some species are successful in invading new environments and others not. Most of our understanding and generalizations thereof, however, are based on studies of plants and animals, and little is known on invasion processes of microorganisms. We conducted a microcosm experiment to understand factors promoting the success of biological invasions of aquatic microorganisms. In a controlled lab experiment, protist and rotifer species originally isolated in North America invaded into a natural, field-collected community of microorganisms of European origin. To identify the importance of environmental disturbances on invasion success, we either repeatedly disturbed the local patches, or kept them as undisturbed controls. We measured both short-term establishment and long-term invasion success, and correlated it with species-specific life-history traits. We found that environmental disturbances significantly affected invasion success. Depending on the invading species' identity, disturbances were either promoting or decreasing invasion success. The interaction between habitat disturbance and species identity was especially pronounced for long-term invasion success. Growth rate was the most important trait promoting invasion success, especially when the species invaded into a disturbed local community. We conclude that neither species traits nor environmental factors alone conclusively predict invasion success, but an integration of both of them is necessary.
From dust to dose: Effects of forest disturbance on increased inhalation exposure.
Whicker, Jeffrey J; Pinder, John E; Breshears, David D; Eberhart, Craig F
2006-09-15
Ecosystem disturbances that remove vegetation and disturb surface soils are major causes of excessive soil erosion and can result in accelerated transport of soils contaminated with hazardous materials. Accelerated wind erosion in disturbed lands that are contaminated is of particular concern because of potential increased inhalation exposure, yet measurements regarding these relationships are lacking. The importance of this was highlighted when, in May of 2000, the Cerro Grande fire burned over roughly 30% of Los Alamos National Laboratory (LANL), mostly in ponderosa pine (Pinus ponderosa) forest, and through areas with soils containing contaminants, particularly excess depleted and natural uranium. Additionally, post-fire thinning was performed in burned and unburned forests on about 25% of LANL land. The first goal of this study was to assess the potential for increased inhalation dose from uranium contaminated soils via wind-driven resuspension of soil following the Cerro Grande Fire and subsequent forest thinning. This was done through analysis of post-disturbance measurements of uranium air concentrations and their relationships with wind velocity and seasonal vegetation cover. We found a 14% average increase in uranium air concentrations at LANL perimeter locations after the fire, and the greatest air concentrations occurred during the months of April-June when wind velocities are highest, no snow cover, and low vegetation cover. The second goal was to develop a methodology to assess the relative contribution of each disturbance type towards increasing public and worker exposure to these resuspended soils. Measurements of wind-driven dust flux in severely burned, moderately burned, thinned, and unburned/unthinned forest areas were used to assess horizontal dust flux (HDF) in these areas. Using empirically derived relationships between measurements of HDF and respirible dust, coupled with onsite uranium soil concentrations, we estimate relative increases in
Li, Shu; Huang, Zheng; Wang, Yi; Liu, Yu-Qing; Luo, Ran; Shang, Jing-Ge; Liao, Qian-Jia-Hua
2018-02-01
In this study, the migration of antibiotics (norfloxacin, NOR; and sulfamethoxazole, SMX) under simulated resuspension conditions across the sediment-water interface were quantified for two locations in China: point A, located in Meiliang Bay of Lake Taihu, and point B, located in Dapukou of Lake Taihu. The concentrations of suspended solids (SS) in the overlying water amounted to 100, 500, and 1000 mg/L during background, moderate, and strong simulated wind-wave disturbances, respectively. At each SS level, the initial concentrations of the two antibiotics were set to 1, 5, and 10 mg/L. The results showed that both resuspended SS and the initial concentration of antibiotics could influence the migration of NOR in the water-sediment system. Specifically, both higher SS and initial antibiotic concentrations were associated with higher rates of migration and accumulation of NOR from water to sediment. In contrast, the migration of SMX in the water-sediment system was not impacted by SS or initial antibiotic concentration. The adsorption capacities of sediments for NOR and SMX were significantly different at both locations, possibly reflecting differences in cation exchange capacity (CEC) and organic material (OM) contents. In general, higher CEC and OM values were found in sediments with a higher adsorption capacity for the antibiotics. When CEC and OM values of sediments were higher, the adsorption capacity reached up to 51.73 mg/kg. Large differences in the migration from water to sediment were observed for the two antibiotics, with NOR migration rates higher than those of SMX. The accumulation of NOR in surface sediment during resuspension was about 14 times higher than that of SMX. The main reason for this is that the chemical adsorption of NOR is seldom reversible. Overall, this study demonstrates that resuspension of NOR and SMX attached to sediments under simulated wind-wave disturbances can promote the migration of the antibiotics from water to sediment
DAC with LQR Control Design for Pitch Regulated Variable Speed Wind Turbine
DEFF Research Database (Denmark)
Imran, Raja Muhammad; Hussain, Dil Muhammad Akbar; Soltani, Mohsen
2014-01-01
Disturbance Accommodation Control (DAC) is used to model and simulate a system with known disturbance waveform. This paper presents a control scheme to mitigate the effect of disturbances by using collective pitch control for the aboverated wind speed (Region III) for a variable speed wind turbine....... We have used Linear Quadratic Regulator (LQR) to obtain full state feedback gain, disturbance feedback gain is calculated independently and then estimator gain is achieved by poleplacement technique in the DAC augmented plant model. The reduced order model (two-mass model) of wind turbine is used...... and 5MW National Renewable Energy Laboratory (NREL) wind turbine is used in this research. We have shown comparison of results relating to pitch angle, drive train torsion and generator speed obtained by a PID controller and DAC. Simulations are performed in MATLAB/Simulink. The results are compared...
Directory of Open Access Journals (Sweden)
Guo Jiuwang
2015-01-01
Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.
Directory of Open Access Journals (Sweden)
Robinson I. Negrón-Juárez
2014-06-01
Full Text Available Topography affects the patterns of forest disturbance produced by tropical cyclones. It determines the degree of exposure of a surface and can alter wind characteristics. Whether multispectral remote sensing data can sense the effect of topography on disturbance is a question that deserves attention given the multi-scale spatial coverage of these data and the projected increase in intensity of the strongest cyclones. Here, multispectral satellite data, topographic maps and cyclone surface wind data were used to study the patterns of disturbance in an Australian rainforest with complex mountainous terrain produced by tropical cyclone Yasi (2011. The cyclone surface wind data (H*wind was produced by the Hurricane Research Division of the National Oceanic and Atmospheric Administration (HRD/NOAA, and this was the first time that this data was produced for a cyclone outside of United States territory. A disturbance map was obtained by applying spectral mixture analyses on satellite data and presented a significant correlation with field-measured tree mortality. Our results showed that, consistent with cyclones in the southern hemisphere, multispectral data revealed that forest disturbance was higher on the left side of the cyclone track. The highest level of forest disturbance occurred in forests along the path of the cyclone track (±30°. Levels of forest disturbance decreased with decreasing slope and with an aspect facing off the track of the cyclone or away from the dominant surface winds. An increase in disturbance with surface elevation was also observed. However, areas affected by the same wind intensity presented increased levels of disturbance with increasing elevation suggesting that complex terrain interactions act to speed up wind at higher elevations. Yasi produced an important offset to Australia’s forest carbon sink in 2010. We concluded that multispectral data was sensitive to the main effects of complex topography on disturbance
A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections
Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.
2014-01-01
A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.
Energy Technology Data Exchange (ETDEWEB)
Peltzer, Inken [Technical University of Berlin, Institute for Aeronautics and Astronautics, Berlin (Germany)
2008-06-15
This paper describes in-flight and wind tunnel research into laminar-turbulent transition. Measurements were carried out with a laminar wing glove for a glider (Twin II Grob G103), which could also be used in the large laminar wind tunnel at the Institute for Aerodynamics and Gasdynamics in Stuttgart. The central aspect of the investigation was the survey of the temporal-spatial development and propagation of natural as well as controlled generated waves. For the experiments performed, varied sensor arrays were used which allowed the two-dimensional acquisition of flow information on the glove (surface hot-wire and piezo foil sensors). Thus the amplification and the spatial distribution of the disturbances could be measured and compared in flight as well as in the wind tunnel, beginning with the very early linear amplification stage to the early non-linear stage of transition. For the investigation of controlled transition, multiple spanwise adjacent harmonic point sources were used which were operated independently. (orig.)
Application of model predictive control for optimal operation of wind turbines
Yuan, Yuan; Cao, Pei; Tang, J.
2017-04-01
For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.
Directory of Open Access Journals (Sweden)
Chih-Chiang Wei
2018-04-01
Full Text Available Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain Range (CMR, the wind speed of typhoons becomes difficult to predict. This research had two primary objectives: (1 to develop data-driven techniques and a powerful artificial neural network (ANN model to predict the highly complex nonlinear wind systems in western Taiwan; and, (2 to investigate the accuracy of wind speed predictions at various locations and for various durations in western Taiwan when the track of westward typhoons is affected by the complex geographical shelters and disturbances of the CMR. This study developed a typhoon wind speed prediction model that evaluated various typhoon tracks (covering Type 2, Type 3, and Type 4 tracks, as defined by the Central Weather Bureau, and evaluated the prediction accuracy at Hsinchu, Wuqi, and Kaohsiung Stations in western Taiwan. Back propagation neural networks (BPNNs were employed to establish wind speed prediction models, and a linear regression model was adopted as the benchmark to evaluate the strengths and weaknesses of the BPNNs. The results were as follows: (1 The BPNNs generally had favorable performance in predicting wind speeds and their performances were superior to linear regressions; (2 when absolute errors were adopted to evaluate the prediction performances, the predictions at Hsinchu Station were the most accurate, whereas those at Wuqi Station were the least accurate; however, when relative errors were adopted, the predictions at Hsinchu Station were again the most accurate, whereas those at Kaohsiung were the least accurate; and, (3 regarding the relative error rates for the maximum wind speed of Types 2, 3, and 4 typhoons, Wuqi, Kaohsiung, and Wuqi had the most accurate performance, respectively; as
Model Predictive Control of Wind Turbines
DEFF Research Database (Denmark)
Henriksen, Lars Christian
Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...
International Nuclear Information System (INIS)
Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.
2014-01-01
Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem
Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms
DEFF Research Database (Denmark)
Asgarpour, Masoud
2017-01-01
monitoring, fault detection and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...
Model predictive control of room temperature with disturbance compensation
Kurilla, Jozef; Hubinský, Peter
2017-08-01
This paper deals with temperature control of multivariable system of office building. The system is simplified to several single input-single output systems by decoupling their mutual linkages, which are separately controlled by regulator based on generalized model predictive control. Main part of this paper focuses on the accuracy of the office temperature with respect to occupancy profile and effect of disturbance. Shifting of desired temperature and changing of weighting coefficients are used to achieve the desired accuracy of regulation. The final structure of regulation joins advantages of distributed computing power and possibility to use network communication between individual controllers to consider the constraints. The advantage of using decoupled MPC controllers compared to conventional PID regulators is demonstrated in a simulation study.
Development of ANN Model for Wind Speed Prediction as a Support for Early Warning System
Directory of Open Access Journals (Sweden)
Ivan Marović
2017-01-01
Full Text Available The impact of natural disasters increases every year with more casualties and damage to property and the environment. Therefore, it is important to prevent consequences by implementation of the early warning system (EWS in order to announce the possibility of the harmful phenomena occurrence. In this paper, focus is placed on the implementation of the EWS on the micro location in order to announce possible harmful phenomena occurrence caused by wind. In order to predict such phenomena (wind speed, an artificial neural network (ANN prediction model is developed. The model is developed on the basis of the input data obtained by local meteorological station on the University of Rijeka campus area in the Republic of Croatia. The prediction model is validated and evaluated by visual and common calculation approaches, after which it was found that it is possible to perform very good wind speed prediction for time steps Δt=1 h, Δt=3 h, and Δt=8 h. The developed model is implemented in the EWS as a decision support for improvement of the existing “procedure plan in a case of the emergency caused by stormy wind or hurricane, snow and occurrence of the ice on the University of Rijeka campus.”
How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?
DEFF Research Database (Denmark)
Murcia Leon, Juan Pablo; Réthoré, Pierre-Elouan; Natarajan, Anand
2015-01-01
(AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses...... distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against...... the traditional binning method with trapezoidal and Simpson's integration rules. The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model...
Prediction of wind energy distribution in complex terrain using CFD
DEFF Research Database (Denmark)
Xu, Chang; Li, Chenqi; Yang, Jianchuan
2013-01-01
Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software ...
Mitigation of Wind Turbine/Vortex Interaction Using Disturbance Accommodating Control
Energy Technology Data Exchange (ETDEWEB)
Hand, M. M.
2003-12-01
Wind turbines, a competitive source of emission-free electricity, are being designed with diameters and hub heights approaching 100 m, to further reduce the cost of the energy they produce. At this height above the ground, the wind turbine is exposed to atmospheric phenomena such as low-level jets, gravity waves, and Kelvin-Helmholtz instabilities, which are not currently modeled in wind turbine design codes. These atmospheric phenomena can generate coherent turbulence that causes high cyclic loads on wind turbine blades. These fluctuating loads lead to fatigue damage accumulation and blade lifetime reduction. Advanced control was used to mitigate vortex-induced blade cyclic loading. A full-state feedback controller that incorporates more detailed vortex inputs achieved significantly greater blade load reduction. Blade loads attributed to vortex passage, then, can be reduced through advanced control, and further reductions appear feasible.
Energy Technology Data Exchange (ETDEWEB)
Zhang, J.; Chowdhury, S.; Messac, A.; Hodge, B. M.
2013-08-01
This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.
Wind power forecast error smoothing within a wind farm
International Nuclear Information System (INIS)
Saleck, Nadja; Bremen, Lueder von
2007-01-01
Smoothing of wind power forecast errors is well-known for large areas. Comparable effects within a wind farm are investigated in this paper. A Neural Network was taken to predict the power output of a wind farm in north-western Germany comprising 17 turbines. A comparison was done between an algorithm that fits mean wind and mean power data of the wind farm and a second algorithm that fits wind and power data individually for each turbine. The evaluation of root mean square errors (RMSE) shows that relative small smoothing effects occur. However, it can be shown for this wind farm that individual calculations have the advantage that only a few turbines are needed to give better results than the use of mean data. Furthermore different results occurred if predicted wind speeds are directly fitted to observed wind power or if predicted wind speeds are first fitted to observed wind speeds and then applied to a power curve. The first approach gives slightly better RMSE values, the bias improves considerably
Impacts of Landscape Context on Patterns of Wind Downfall Damage in a Fragmented Amazonian Landscape
Schwartz, N.; Uriarte, M.; DeFries, R. S.; Gutierrez-Velez, V. H.; Fernandes, K.; Pinedo-Vasquez, M.
2015-12-01
Wind is a major disturbance in the Amazon and has both short-term impacts and lasting legacies in tropical forests. Observed patterns of damage across landscapes result from differences in wind exposure and stand characteristics, such as tree stature, species traits, successional age, and fragmentation. Wind disturbance has important consequences for biomass dynamics in Amazonian forests, and understanding the spatial distribution and size of impacts is necessary to quantify the effects on carbon dynamics. In November 2013, a mesoscale convective system was observed over the study area in Ucayali, Peru, a highly human modified and fragmented forest landscape. We mapped downfall damage associated with the storm in order to ask: how does the severity of damage vary within forest patches, and across forest patches of different sizes and successional ages? We applied spectral mixture analysis to Landsat images from 2013 and 2014 to calculate the change in non-photosynthetic vegetation fraction after the storm, and combined it with C-band SAR data from the Sentinel-1 satellite to predict downfall damage measured in 30 field plots using random forest regression. We then applied this model to map damage in forests across the study area. Using a land cover classification developed in a previous study, we mapped secondary and mature forest, and compared the severity of damage in the two. We found that damage was on average higher in secondary forests, but patterns varied spatially. This study demonstrates the utility of using multiple sources of satellite data for mapping wind disturbance, and adds to our understanding of the sources of variation in wind-related damage. Ultimately, an improved ability to map wind impacts and a better understanding of their spatial patterns can contribute to better quantification of carbon dynamics in Amazonian landscapes.
International Nuclear Information System (INIS)
Elnaggar, M.; Abdel Fattah, H.A.; Elshafei, A.L.
2014-01-01
This paper presents a complete design of a two-level control system to capture maximum power in wind energy conversion systems. The upper level of the proposed control system adopts a modified line search optimization algorithm to determine a setpoint for the wind turbine speed. The calculated speed setpoint corresponds to the maximum power point at given operating conditions. The speed setpoint is fed to a generalized predictive controller at the lower level of the control system. A different formulation, that treats the aerodynamic torque as a disturbance, is postulated to derive the control law. The objective is to accurately track the setpoint while keeping the control action free from unacceptably fast or frequent variations. Simulation results based on a realistic model of a 1.5 MW wind turbine confirm the superiority of the proposed control scheme to the conventional ones. - Highlights: • The structure of a MPPT (maximum power point tracking) scheme is presented. • The scheme is divided into the optimization algorithm and the tracking controller. • The optimization algorithm is based on an online line search numerical algorithm. • The tracking controller is treating the aerodynamics torque as a loop disturbance. • The control technique is simulated with stochastic wind speed by Simulink and FAST
International Nuclear Information System (INIS)
Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor
2017-01-01
Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the
Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen
1999-01-01
Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.
The effect of the Sep wind park near Oosterbierum, Friesland, The Netherlands, on birds
International Nuclear Information System (INIS)
Winkelman, J.E.
1992-01-01
The title study concerns the period 1984-1991. The wind park consists of 18 three-bladed 300 kW horizontal axis wind turbines of 35 meters height, and a rotor diameter of 30 meters, seven meteorological towers, and three cluster and control buildings. Aspects studied included disturbance of breeding, resting or feeding, and migrating birds, behavior of birds approaching the wind turbines during the day and night, and bird victims due to collision with the wind turbines and the meteorological towers. In this report attention is paid to the disturbance of the bird's biotope. The results show that four species of grassland birds, breeding in the park, were hardly disturbed by the wind turbines. For feeding and resting birds, however, disturbance effects were noted, even at a distance of 500 meters from the outside wind turbine array. The present number of bird species reduced 60-95%, dependent on the species, after the wind park was put into operation. Also the behavior of migrating birds was influenced by the wind park, showed in clustering of groups or avoiding the wind park, sometimes up to 67% of the birds did so. It is therefore recommended not to implement new wind parks in important bird migration and bird feeding or bird resting areas. Bird popular areas, however, are mostly windy areas. 15 figs., 25 tabs., 56 app., 128 refs
Evolution Of The Cloud Field And Wind Structure Of Ntb Disturbance
Barrado-Izagirre, Naiara; Pérez-Hoyos, S.; García-Melendo, E.; Sánchez-Lavega, A.
2009-09-01
The banded visual aspect of cloud patterns in Jupiter hides markedly turbulent areas visible in high resolution images. The North Temperate Belt (NTB) at 21° N planetocentric latitude where the most intense Jovian jet resides (with speeds of 160 - 180 m/s) is a region of particular interest because it is known to suffer almost every 15 years an eruption or disturbance which dramatically changes its appearance. This phenomenon is known as NTB Disturbance (NTBD). The last one of such disturbances happened in 2007 and was captured by the Hubble Space Telescope and with lower resolution by the "International Outer Planet Watch” (IOPW) network [Sánchez-Lavega et al., 2008. Depth of a strong Jovian jet from a planetary-scale disturbance driven by storms, Nature 451.]. In this work we make use of these observations to characterize the morphology of the disturbed cloud field in the wake of the plumes which originated the perturbation. This is done mostly in terms of the brightness spectral distribution in order to characterize the typical spatial frequency of the perturbation and its wavy and turbulent nature. In addition we make a comparison of the jet profile in the NTB just after the disturbance ended (June 2007) with one obtained year later (July 2008). It shows that a change occurred in its anticyclonic side producing a reinforced westward jet at 17°N with a speed change of 30 m/s. Acknowledgments: This work has been funded by Spanish MEC AYA2006-07735 with FEDER support and Grupos Gobierno Vasco IT-464-07
Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model
Directory of Open Access Journals (Sweden)
Erasmo Cadenas
2016-02-01
Full Text Available Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA. This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX. This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.
An integrated control method for a wind farm to reduce frequency deviations in a small power system
International Nuclear Information System (INIS)
Kaneko, Toshiaki; Uehara, Akie; Senjyu, Tomonobu; Yona, Atsushi; Urasaki, Naomitsu
2011-01-01
Output power of wind turbine generator (WTG) is not constant and fluctuates due to wind speed changes. To reduce the adverse effects of the power system introducing WTGs, there are several published reports on output power control of WTGs detailing various researches based on pitch angle control, variable speed wind turbines, energy storage systems, and so on. In this context, this paper presents an integrated control method for a WF to reduce frequency deviations in a small power system. In this study, the WF achieves the frequency control with two control schemes: load estimation and short-term ahead wind speed prediction. For load estimation in the small power system, a minimal-order observer is used as disturbance observer. The estimated load is utilized to determine the output power command of the WF. To regulate the output power command of the WF according to wind speed changing, short-term ahead wind speed is predicted by using least-squares method. The predicted wind speed adjusts the output power command of the WF as a multiplying factor with fuzzy reasoning. By means of the proposed method, the WF can operate according to the wind and load conditions. In the WF system, each output power of the WTGs is controlled by regulating each pitch angle. For increasing acquisition power of the WF, a dispatch control method also is proposed. In the pitch angle control system of each WTG, generalized predictive control (GPC) is applied to enhance the control performance. Effectiveness of the proposed method is verified by the numerical simulations.
Optimal control for wind turbine system via state-space method
Shanoob, Mudhafar L.
Renewable energy is becoming a fascinating research interest in future energy production because it is green and does not pollute nature. Wind energy is an excellent example of renewable resources that are evolving. Throughout the history of humanity, wind energy has been used. In ancient time, it was used to grind seeds, sailing etc. Nowadays, wind energy has been used to generate electrical power. Researchers have done a lot of research about using a wind source to generate electricity. As wind flow is not reliable, there is a challenge to get stable electricity out of this varying wind. This problem leads to the use of different control methods and the optimization of these methods to get a stable and reliable electrical energy. In this research, a wind turbine system is considered to study the transient and the steady-state stability; consisting of the aerodynamic system, drive train and generator. The Doubly Feed Induction Generator (DFIG) type generator is used in this thesis. The wind turbine system is connected to power system network. The grid is an infinite bus bar connected to a short transmission line and transformer. The generator is attached to the grid from the stator side. State-space method is used to model the wind turbine parts. The system is modeled and controlled using MATLAB/Simulation software. First, the current-mode control method (PVdq) with (PI) regulator is operated as a reference to find how the system reacts to an unexpected disturbance on the grid side or turbine side. The controller is operated with three scenarios of disruption: Disturbance-mechanical torque input, Step disturbance in the electrical torque reference and Fault Ride-through. In the simulation results, the time response and the transient stability of the system is a product of the disturbances that take a long time to settle. So, for this reason, Linear Quadratic Regulation (LQR) optimal control is utilized to solve this problem. The LQR method is designed based on
Methodology for Assessment of Inertial Response from Wind Power Plants
DEFF Research Database (Denmark)
Altin, Müfit; Teodorescu, Remus; Bak-Jensen, Birgitte
2012-01-01
High wind power penetration levels result in additional requirements from wind power in order to improve frequency stability. Replacement of conventional power plants with wind power plants reduces the power system inertia due to the wind turbine technology. Consequently, the rate of change...... of frequency and the maximum frequency deviation increase after a disturbance such as generation loss, load increase, etc. Having no inherent inertial response, wind power plants need additional control concepts in order to provide an additional active power following a disturbance. Several control concepts...... have been implemented in the literature, but the assessment of these control concepts with respect to power system requirements has not been specified. In this paper, a methodology to assess the inertial response from wind power plants is proposed. Accordingly, the proposed methodology is applied...
New, Leslie; Bjerre, Emily; Millsap, Brian; Otto, Mark C; Runge, Michael C
2015-01-01
Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6
Modeling, simulating and validating wind turbine behavior during grid disturbances
Coster, E.J.; Ishchenko, A.; Myrzik, J.M.A.; Kling, W.L.
2007-01-01
Due to the liberalized energy market Distributed Generation, DG, is increasing. At this moment, most of the power produced by DG, is generated by CHP-plants and variable speed wind turbines. Integration of wind turbines have impact on several aspects of power systems such as power system stability,
Parrish, Judith T.; Peterson, F.
1988-01-01
Wind directions for Middle Pennsylvanian through Jurassic time are predicted from global circulation models for the western United States. These predictions are compared with paleowind directions interpreted from eolian sandstones of Middle Pennsylvanian through Jurassic age. Predicted regional wind directions correspond with at least three-quarters of the paleowind data from the sandstones; the rest of the data may indicate problems with correlation, local effects of paleogeography on winds, and lack of resolution of the circulation models. The data and predictions suggest the following paleoclimatic developments through the time interval studied: predominance of winter subtropical high-pressure circulation in the Late Pennsylvanian; predominance of summer subtropical high-pressure circulation in the Permian; predominance of summer monsoonal circulation in the Triassic and earliest Jurassic; and, during the remainder of the Jurassic, influence of both summer subtropical and summer monsoonal circulation, with the boundary between the two systems over the western United States. This sequence of climatic changes is largely owing to paleogeographic changes, which influenced the buildup and breakdown of the monsoonal circulation, and possibly owing partly to a decrease in the global temperature gradient, which might have lessened the influence of the subtropical high-pressure circulation. The atypical humidity of Triassic time probably resulted from the monsoonal circulation created by the geography of Pangaea. This circulation is predicted to have been at a maximum in the Triassic and was likely to have been powerful enough to draw moisture along the equator from the ocean to the west. ?? 1988.
Predicting hurricane wind damage by claim payout based on Hurricane Ike in Texas
Directory of Open Access Journals (Sweden)
Ji-Myong Kim
2016-09-01
Full Text Available The increasing occurrence of natural disasters and their related damage have led to a growing demand for models that predict financial loss. Although considerable research on the financial losses related to natural disasters has found significant predictors, there has been a lack of comprehensive study that addresses the relationship among vulnerabilities, natural disasters, and the economic losses of individual buildings. This study identifies the vulnerability indicators for hurricanes to establish a metric to predict the related financial loss. We classify hurricane-prone areas by highlighting the spatial distribution of losses and vulnerabilities. This study used a Geographical Information System (GIS to combine and produce spatial data and a multiple regression method to establish a wind damage prediction model. As the dependent variable, we used the value of the Texas Windstorm Insurance Association (TWIA claim payout divided by the appraised values of the buildings to predict real economic loss. As independent variables, we selected a hurricane indicator and built environment vulnerability indicators. The model we developed can be used by government agencies and insurance companies to predict hurricane wind damage.
Wind Turbine Acoustic Investigation: Infrasound and Low-Frequency Noise--A Case Study
Ambrose, Stephen E.; Rand, Robert W.; Krogh, Carmen M. E.
2012-01-01
Wind turbines produce sound that is capable of disturbing local residents and is reported to cause annoyance, sleep disturbance, and other health-related impacts. An acoustical study was conducted to investigate the presence of infrasonic and low-frequency noise emissions from wind turbines located in Falmouth, Massachusetts, USA. During the…
Energy Technology Data Exchange (ETDEWEB)
Curry, Charles L. [Canadian Centre for Climate Modelling and Analysis, Environment Canada, University of Victoria, Victoria, BC (Canada); School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada); Kamp, Derek van der [School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada); Pacific Climate Impacts Consortium, University of Victoria, Victoria, BC (Canada); Monahan, Adam H. [School of Earth and Ocean Sciences, University of Victoria, Victoria, BC (Canada)
2012-04-15
Surface wind speed is a key climatic variable of interest in many applications, including assessments of storm-related infrastructure damage and feasibility studies of wind power generation. In this work and a companion paper (van der Kamp et al. 2011), the relationship between local surface wind and large-scale climate variables was studied using multiple regression analysis. The analysis was performed using monthly mean station data from British Columbia, Canada and large-scale climate variables (predictors) from the NCEP-2 reanalysis over the period 1979-2006. Two regression-based methodologies were compared. The first relates the annual cycle of station wind speed to that of the large-scale predictors at the closest grid box to the station. It is shown that the relatively high correlation coefficients obtained with this method are attributable to the dominant influence of region-wide seasonality, and thus contain minimal information about local wind behaviour at the stations. The second method uses interannually varying data for individual months, aggregated into seasons, and is demonstrated to contain intrinsically local information about the surface winds. The dependence of local wind speed upon large-scale predictors over a much larger region surrounding the station was also explored, resulting in 2D maps of spatial correlations. The cross-validated explained variance using the interannual method was highest in autumn and winter, ranging from 30 to 70% at about a dozen stations in the region. Reasons for the limited predictive skill of the regressions and directions for future progress are reviewed. (orig.)
International Nuclear Information System (INIS)
Liu, Hui; Tian, Hong-qi; Li, Yan-fei
2015-01-01
Highlights: • Four algorithms [EMD/FEEMD/WD/WPD] are proposed for the wind speed decomposition. • Two new hybrid forecasting algorithms [FEEMD-MLP/ANFIS] are presented. • The contributions of the FEEMD/WPD algorithms are both significant. • The MLP has better forecasting performance than the ANFIS in these cases. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. Compared to the single algorithms, the hybrid ones always have better performance in the wind speed predictions. In this paper, three most important decomposing algorithms [Wavelet Decomposition – WD/Wavelet Packet Decomposition – WPD/Empirical Mode Decomposition – EMD] and a latest decomposing algorithm [Fast Ensemble Empirical Mode Decomposition – FEEMD] are all adopted to realize the wind speed high-precision predictions with two representative networks [MLP Neural Network/ANFIS Neural Network]. Based on the hybrid forecasting framework, two new wind speed forecasting methods [FEEMD-MLP and FEEMD-ANFIS] are proposed. Additionally, a series of performance comparison is provided, which includes EMD-MLP, FEEMD-MLP, EDM-ANFIS, FEEMD-ANFIS, WD-MLP, WD-ANFIS, WPD-MLP and WPD-ANFIS. The aim of the study is to investigate the decomposing and forecasting performance of the different hybrid models. Two experimental results show that: (1) Due to the inclusion of the decomposing algorithms, the hybrid ANN algorithms have better performance than their corresponding single ANN algorithms; (2) the proposed new FEEMD-MLP hybrid model has the best performance in the three-step predictions while the WPD-MLP hybrid model has the best performance in the one-step predictions; (3) among the decomposing algorithms, the FEEMD and WPD have better performance than the EMD and WD, respectively; (4) in the forecasting neural networks, the MLP has better performance
Directory of Open Access Journals (Sweden)
Philipp Sterzer
2016-10-01
Full Text Available Current theories in the framework of hierarchical predictive coding propose that positive symptoms of schizophrenia, such as delusions and hallucinations, arise from an alteration in Bayesian inference, the term inference referring to a process by which learned predictions are used to infer probable causes of sensory data. However, for one particularly striking and frequent symptom of schizophrenia, thought insertion, no plausible account has been proposed in terms of the predictive-coding framework. Here we propose that thought insertion is due to an altered experience of thoughts as coming from nowhere, as is already indicated by the early 20th century phenomenological accounts by the early Heidelberg School of psychiatry. These accounts identified thought insertion as one of the self-disturbances (from German: Ichstörungen of schizophrenia and used mescaline as a model-psychosis in healthy individuals to explore the possible mechanisms. The early Heidelberg School (Gruhle, Mayer-Gross, Beringer first named and defined the self-disturbances, and proposed that thought insertion involves a disruption of the inner connectedness of thoughts and experiences, and a becoming sensory of those thoughts experienced as inserted. This account offers a novel way to integrate the phenomenology of thought insertion with the predictive coding framework. We argue that the altered experience of thoughts may be caused by a reduced precision of context-dependent predictions, relative to sensory precision. According to the principles of Bayesian inference, this reduced precision leads to increased prediction-error signals evoked by the neural activity that encodes thoughts. Thus, in analogy with the prediction-error related aberrant salience of external events that has been proposed previously, internal events such as thoughts (including volitions, emotions and memories can also be associated with increased prediction-error signaling and are thus imbued with
Health-aware Model Predictive Control of Wind Turbines using Fatigue Prognosis
DEFF Research Database (Denmark)
Sardi, Hector Eloy Sanchez; Escobet, Teressa; Puig, Vicenc
2015-01-01
management module with the control provides a mechanism for the wind turbine to operate safely and optimize the trade-off between components life and energy production. The research presented in this paper explores the integration of model predictive control (MPC) with fatigue-based prognosis approach...
International Nuclear Information System (INIS)
2009-06-01
The authors report a study which aimed at exploiting and deepening the results of a 2001 survey on visual and sound disturbances caused by wind turbines in Sigean (Aude), at identifying all the attitudes and opinions with respect with wind energy, and at assessing the different characteristics of a wind farm (height, localization, and so on). A survey has been performed on four sites located in different French regions. The authors discuss the social-demographic characteristics of the population samples, the global opinion on wind energy, and the opinion of the people on wind turbines located in their neighbourhood. They propose an estimation of benefits and damages related to the vicinity of wind turbines. By applying a method of choice experiments, they reveal the preferences of residents
Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W
2013-01-01
Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with soils, and this pattern was exaggerated following disturbance. Degradation with and without MAP was predictable by initial bacterial diversity and the abundance of specific assemblages of Betaproteobacteria, respectively. High Betaproteobacteria abundance was positively correlated with high diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future. PMID:23389106
Energy Technology Data Exchange (ETDEWEB)
Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.
2014-06-01
Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.
International Nuclear Information System (INIS)
Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli
2016-01-01
Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid
Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui
2017-01-01
This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....
Observations and Predictability of Gap Winds in the Salmon River Canyon of Central Idaho, USA
Directory of Open Access Journals (Sweden)
Natalie S. Wagenbrenner
2018-01-01
Full Text Available This work investigates gap winds in a steep, deep river canyon prone to wildland fire. The driving mechanisms and the potential for forecasting the gap winds are investigated. The onset and strength of the gap winds are found to be correlated to the formation of an along-gap pressure gradient linked to periodic development of a thermal trough in the Pacific Northwest, USA. Numerical simulations are performed using a reanalysis dataset to investigate the ability of numerical weather prediction (NWP to simulate the observed gap wind events, including the timing and flow characteristics within the canyon. The effects of model horizontal grid spacing and terrain representation are considered. The reanalysis simulations suggest that horizontal grid spacings used in operational NWP could be sufficient for simulating the gap flow events given the regional-scale depression in which the Salmon River Canyon is situated. The strength of the events, however, is under-predicted due, at least in part, to terrain smoothing in the model. Routine NWP, however, is found to have mixed results in terms of forecasting the gap wind events, primarily due to problems in simulating the regional sea level pressure system correctly.
Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system
International Nuclear Information System (INIS)
Messadi, Manal; Mellit, Adel; Kemih, Karim; Ghanes, Malek
2015-01-01
This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. (paper)
International Nuclear Information System (INIS)
Ljunggren, S.
2001-12-01
First, the generation of noise at wind power plants and the character of the sound is described. The propagation of the sound and its dependence on the structure of the ground and on wind and temperature is treated next. Models for calculation of the noise emission are reviewed and examples of applications are given. Different means for reducing the disturbances are described
Win-win for wind and wildlife: a vision to facilitate sustainable development.
Kiesecker, Joseph M; Evans, Jeffrey S; Fargione, Joe; Doherty, Kevin; Foresman, Kerry R; Kunz, Thomas H; Naugle, Dave; Nibbelink, Nathan P; Niemuth, Neal D
2011-04-13
Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW) than most other forms of energy production, making appropriate siting and mitigation particularly important. Species that require large unfragmented habitats and those known to avoid vertical structures are particularly at risk from wind development. Developing energy on disturbed lands rather than placing new developments within large and intact habitats would reduce cumulative impacts to wildlife. The U.S. Department of Energy estimates that it will take 241 GW of terrestrial based wind development on approximately 5 million hectares to reach 20% electricity production for the U.S. by 2030. We estimate there are ∼7,700 GW of potential wind energy available across the U.S., with ∼3,500 GW on disturbed lands. In addition, a disturbance-focused development strategy would avert the development of ∼2.3 million hectares of undisturbed lands while generating the same amount of energy as development based solely on maximizing wind potential. Wind subsidies targeted at favoring low-impact developments and creating avoidance and mitigation requirements that raise the costs for projects impacting sensitive lands could improve public value for both wind energy and biodiversity conservation.
Win-win for wind and wildlife: a vision to facilitate sustainable development.
Directory of Open Access Journals (Sweden)
Joseph M Kiesecker
Full Text Available Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW than most other forms of energy production, making appropriate siting and mitigation particularly important. Species that require large unfragmented habitats and those known to avoid vertical structures are particularly at risk from wind development. Developing energy on disturbed lands rather than placing new developments within large and intact habitats would reduce cumulative impacts to wildlife. The U.S. Department of Energy estimates that it will take 241 GW of terrestrial based wind development on approximately 5 million hectares to reach 20% electricity production for the U.S. by 2030. We estimate there are ∼7,700 GW of potential wind energy available across the U.S., with ∼3,500 GW on disturbed lands. In addition, a disturbance-focused development strategy would avert the development of ∼2.3 million hectares of undisturbed lands while generating the same amount of energy as development based solely on maximizing wind potential. Wind subsidies targeted at favoring low-impact developments and creating avoidance and mitigation requirements that raise the costs for projects impacting sensitive lands could improve public value for both wind energy and biodiversity conservation.
Garcia-Melendo, E.; Legarreta, J.; Sanchez-Lavega, A.
2012-12-01
Direct measurements of the structure of the zonal winds of Jupiter and Saturn below the upper cloud layer are very difficult to retrieve. Except from the vertical profile at a Jupiter hot spot obtained from the Galileo probe in 1995 and measurements from cloud tracking by Cassini instruments just below the upper cloud, no other data are available. We present here our inferences of the vertical structure of Jupiter and Saturn zonal wind across the upper troposphere (deep down to about 10 bar level) obtained from nonlinear simulations using the EPIC code of the stability and interactions of large-scale vortices and planetary-scale disturbances in both planets. Acknowledgements: This work has been funded by Spanish MICIIN AYA2009-10701 with FEDER support, Grupos Gobierno Vasco IT-464-07 and UPV/EHU UFI11/55. [1] García-Melendo E., Sánchez-Lavega A., Dowling T.., Icarus, 176, 272-282 (2005). [2] García-Melendo E., Sánchez-Lavega A., Hueso R., Icarus, 191, 665-677 (2007). [3] Sánchez-Lavega A., et al., Nature, 451, 437- 440 (2008). [4] Sánchez-Lavega A., et al., Nature, 475, 71-74 (2011).
Neural network feedforward control of a closed-circuit wind tunnel
Sutcliffe, Peter
Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the
From dust to dose: Effects of forest disturbance on increased inhalation exposure
International Nuclear Information System (INIS)
Whicker, Jeffrey J.; Pinder, John E.; Breshears, David D.; Eberhart, Craig F.
2006-01-01
Ecosystem disturbances that remove vegetation and disturb surface soils are major causes of excessive soil erosion and can result in accelerated transport of soils contaminated with hazardous materials. Accelerated wind erosion in disturbed lands that are contaminated is of particular concern because of potential increased inhalation exposure, yet measurements regarding these relationships are lacking. The importance of this was highlighted when, in May of 2000, the Cerro Grande fire burned over roughly 30% of Los Alamos National Laboratory (LANL), mostly in ponderosa pine (Pinus ponderosa) forest, and through areas with soils containing contaminants, particularly excess depleted and natural uranium. Additionally, post-fire thinning was performed in burned and unburned forests on about 25% of LANL land. The first goal of this study was to assess the potential for increased inhalation dose from uranium contaminated soils via wind-driven resuspension of soil following the Cerro Grande Fire and subsequent forest thinning. This was done through analysis of post-disturbance measurements of uranium air concentrations and their relationships with wind velocity and seasonal vegetation cover. We found a 14% average increase in uranium air concentrations at LANL perimeter locations after the fire, and the greatest air concentrations occurred during the months of April-June when wind velocities are highest, no snow cover, and low vegetation cover. The second goal was to develop a methodology to assess the relative contribution of each disturbance type towards increasing public and worker exposure to these resuspended soils. Measurements of wind-driven dust flux in severely burned, moderately burned, thinned, and unburned/unthinned forest areas were used to assess horizontal dust flux (HDF) in these areas. Using empirically derived relationships between measurements of HDF and respirible dust, coupled with onsite uranium soil concentrations, we estimate relative increases in
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-03-01
Described herein are the FY 1998 results of the study on local wind resource prediction model. The local wind resource prediction models developed so far apply the solutions based on the existing linear models (WASP and AVENU) for relatively flat terrain. These models are studied for their applicability limits. The study covers wind direction and speed patterns of the surface wind and upper winds at 3 sites in Hokkaido, Fukushima Pref. and Shizuoka Pref. The surface winds are found to be correlated with the upper winds both for wind direction and wind speed in almost all cases. Next, wind resources simulations are carried out for each of the classified weather patterns using the existing models, and the prediction errors are studied. The results show that the prediction accuracy of the existing linear models is highly dependent on inputs of observed data, and that the accuracy tends to decrease for the situations where the upper and surface wind conditions greatly differ from each other, as in the case of a land and sea breeze of thermal origin. It is also confirmed that prediction accuracy is lower on complex terrain than on flat terrain. (NEDO)
Predicting Ionization Rates from SEP and Solar Wind Proton Precipitation into the Martian Atmosphere
Jolitz, R.; Dong, C.; Lee, C. O.; Curry, S.; Lillis, R. J.; Brain, D.; Halekas, J. S.; Larson, D. E.; Bougher, S. W.; Jakosky, B. M.
2017-12-01
Precipitating energetic particles ionize planetary atmospheres and increase total electron content. At Mars, the solar wind and solar energetic particles (SEPs) can precipitate directly into the atmosphere because solar wind protons can charge exchange to become neutrals and pass through the magnetosheath, while SEPs are sufficiently energetic to cross the magnetosheath unchanged. In this study we will present predicted ionization rates and resulting electron densities produced by solar wind and SEP proton ionization during nominal solar activity and a CME shock front impact event on May 16 2016. We will use the Atmospheric Scattering of Protons and Energetic Neutrals (ASPEN) model to compare ionization by SEP and solar wind protons currently measured by the SWIA (Solar Wind Ion Analyzer) and SEP instruments aboard the MAVEN spacecraft. Results will help to quantify how the ionosphere responds to extreme solar events during solar minimum.
A prediction model for wind speed ratios at pedestrian level with simplified urban canopies
Ikegaya, N.; Ikeda, Y.; Hagishima, A.; Razak, A. A.; Tanimoto, J.
2017-02-01
The purpose of this study is to review and improve prediction models for wind speed ratios at pedestrian level with simplified urban canopies. We adopted an extensive database of velocity fields under various conditions for arrays consisting of cubes, slender or flattened rectangles, and rectangles with varying roughness heights. Conclusions are summarized as follows: first, a new geometric parameter is introduced as a function of the plan area index and the aspect ratio so as to express the increase in virtual density that causes wind speed reduction. Second, the estimated wind speed ratios in the range 0.05 coefficients between the wind speeds averaged over the entire region, and the front or side region values are larger than 0.8. In contrast, in areas where the influence of roughness elements is significant, such as behind a building, the wind speeds are weakly correlated.
Wind field forecast for accidental release of radiative materials
International Nuclear Information System (INIS)
Kang Ling; Chen Jiayi; Cai Xuhui
2003-01-01
A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area
How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?
International Nuclear Information System (INIS)
Murcia, J P; Réthoré, P E; Natarajan, A; Sørensen, J D
2015-01-01
Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules.The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case. (paper)
International Nuclear Information System (INIS)
Gosling, J.T.; McComas, D.J.; Phillips, J.L.; Bame, S.J.
1991-01-01
Previous work indicates that virtually all transient shock wave disturbances in the solar wind are driven by fast coronal mass ejection events (CMEs). Using a recently appreciated capability for distinguishing CMEs in solar wind data in the form of counterstreaming solar wind electron events, this paper explores the overall effectiveness of shock wave disturbances and CMEs in general in stimulating geomagnetic activity. The study is confined to the interval from mid-August 1978 through mid-October 1982, spanning the last solar activity maximum, when ISEE 3 was in orbit about the L1 Lagrange point 220 R e upstream from Earth. The authors find that all but one of the 37 largest geomagnetic storms in that era were associated with Earth passage of CMEs and/or shock disturbances, with the large majority of these storms being associated with interplanetary events where Earth encountered both a shock and the CME driving the shock (shock/CME events). Although CMEs and/or shock disturbances were increasingly the cause of geomagnetic activity as the level of geomagnetic activity increased, many smaller geomagnetic disturbances were unrelated to these events. Further, approximately half of all CMEs and half of all shock disturbances encountered by Earth did not produce any substantial geomagnetic activity as measured by the planetary geomagnetic index Kp. The geomagnetic effectiveness of Earth directed CMEs and shock wave disturbances was directly related to the flow speed, the magnetic field magnitude, and the strength of the southward (GSM) field component associated with the events. The initial speed of a CME close to the Sun appears to be the most crucial factor in determining if an earthward directed event will be effective in exciting a large geomagnetic disturbance
Hanson, Jacob J; Lorimer, Craig G
2007-07-01
Moderate-severity disturbances appear to be common throughout much of North America, but they have received relatively little detailed study compared to catastrophic disturbances and small gap dynamics. In this study, we examined the immediate impact of moderate-intensity wind storms on stand structure, opening sizes, and light regimes in three hemlock-hardwood forests of northeastern Wisconsin. These were compared to three stands managed by single-tree and group selection, the predominant forest management system for northern hardwoods in the region. Wind storms removed an average of 41% of the stand basal area, compared to 27% removed by uneven-aged harvests, but both disturbances removed trees from a wide range of size classes. The removal of nearly half of the large trees by wind in two old-growth stands caused partial retrogression to mature forest structure, which has been hypothesized to be a major disturbance pathway in the region. Wind storms resulted in residual stand conditions that were much more heterogeneous than in managed stands. Gap sizes ranged from less than 10 m2 up to 5000 m2 in wind-disturbed stands, whereas the largest opening observed in managed stands was only 200 m2. Wind-disturbed stands had, on average, double the available solar radiation at the forest floor compared to managed stands. Solar radiation levels were also more heterogeneous in wind-disturbed stands, with six times more variability at small scales (0.1225 ha) and 15 times more variability at the whole-stand level. Modification of uneven-aged management regimes to include occasional harvests of variable intensity and spatial pattern may help avoid the decline in species diversity that tends to occur after many decades of conventional uneven-aged management. At the same time, a multi-cohort system with these properties would retain a high degree of average crown cover, promote structural heterogeneity typical of old-growth forests, and maintain dominance by late
Musick, H. Brad
1993-01-01
The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.
Directory of Open Access Journals (Sweden)
R. Romero
2005-01-01
uncertainty in the representation of the upper-level disturbance and the necessity to cope with it within the operational context when attempting to issue short to mid-range numerical weather predictions of these high impact weather events, a systematic exploration of the predictability of the three selected case studies subject to uncertainties in the representation of the upper-level precursor disturbance is carried out in this paper. The study is based on an ensemble of mesoscale numerical simulations of each event with the MM5 non-hydrostatic model after perturbing in a systematic way the upper-level disturbance, in the sense of displacing slightly this disturbance upstream/downstream along the zonal direction and intensifying/weakening its amplitude. These perturbations are guided by a previous application of the MM5-adjoint model, which consistently shows high sensitivities of the dynamical control of the heavy rain to the flow configuration about the upper-level disturbance on the day before, thus confirming the precursor characteristics of this agent. The perturbations are introduced to the initial conditions by applying a potential vorticity (PV inversion procedure to the positive PV anomaly associated with the upper-level disturbance, and then using the inverted fields (wind, temperature and geopotential to modify under a physically consistent balance the model initial fields. The results generally show that the events dominated by mesoscale low-level disturbances (Catalogne and last stage of the Piémont episode are very sensitive to the initial uncertainties, such that the heavy rain location and magnitude are in some of the experiments strongly changed in response to the 'forecast errors' of the cyclone trajectory, intensity, shape and translational speed. In contrast, the other situations (Cévennes and initial stage of the Piémont episode, dominated by a larger scale system wich basically acts to guarantee the establishment and persistence of the southerly LLJ
Integrated analysis of wind turbines - The impact of power systems on wind turbine design
DEFF Research Database (Denmark)
Barahona Garzón, Braulio
Megawatt-size wind turbines nowadays operate in very complex environmental conditions, and increasingly demanding power system requirements. Pursuing a cost-effective and reliable wind turbine design is a multidisciplinary task. However nowadays, wind turbine design and research areas...... conditions that stem from disturbances in the power system. An integrated simulation environment, wind turbine models, and power system models are developed in order to take an integral perspective that considers the most important aeroelastic, structural, electrical, and control dynamics. Applications...... of the integrated simulation environment are presented. The analysis of an asynchronous machine, and numerical simulations of a fixedspeed wind turbine in the integrated simulation environment, demonstrate the effects on structural loads of including the generator rotor fluxes dynamics in aeroelastic studies. Power...
Gain-scheduled Linear Quadratic Control of Wind Turbines Operating at High Wind Speed
DEFF Research Database (Denmark)
Østergaard, Kasper Zinck; Stoustrup, Jakob; Brath, Per
2007-01-01
This paper addresses state estimation and linear quadratic (LQ) control of variable speed variable pitch wind turbines. On the basis of a nonlinear model of a wind turbine, a set of operating conditions is identified and a LQ controller is designed for each operating point. The controller gains...... are then interpolated linearly to get a control law for the entire operating envelope. A nonlinear state estimator is designed as a combination of two unscented Kalman filters and a linear disturbance estimator. The gain-scheduling variable (wind speed) is then calculated from the output of these state estimators...
Bongers, F.; Poorter, L.; Hawthorne, W.D.; Sheil, D.
2009-01-01
The intermediate disturbance hypothesis (IDH) predicts local species diversity to be maximal at an intermediate level of disturbance. Developed to explain species maintenance and diversity patterns in species-rich ecosystems such as tropical forests, tests of IDH in tropical forest remain scarce,
A disturbance decoupling nonlinear control law for variable speed wind turbines
DEFF Research Database (Denmark)
Thomsen, Sven Creutz; Poulsen, Niels Kjølstad
2007-01-01
This paper describes a nonlinear control law for controlling variable speed wind turbines using feedback linearization. The novel aspect of the control law is its ability to decouple the effect of wind fluctuations. Furthermore, the transformation to feedback linearizable coordinates is chosen...
International Nuclear Information System (INIS)
2009-04-01
The author proposes a synthesis of a survey performed on four wind farms located in different French regions. It appears that only 5 % of residents feel that wind turbines are disturbing, that a dismantling would be detrimental to the resident well-being, that site expansions are well perceived in terms of social well-being, that residents do not really prefer small wind farms. The author outlines that the obtained results cannot be applied to other sites
International Nuclear Information System (INIS)
Díaz, Santiago; Carta, José A.; Matías, José M.
2017-01-01
Highlights: • Eight measure-correlate-predict (MCP) models used to estimate the wind power densities (WPDs) at a target site are compared. • Support vector regressions are used as the main prediction techniques in the proposed MCPs. • The most precise MCP uses two sub-models which predict wind speed and air density in an unlinked manner. • The most precise model allows to construct a bivariable (wind speed and air density) WPD probability density function. • MCP models trained to minimise wind speed prediction error do not minimise WPD prediction error. - Abstract: The long-term annual mean wind power density (WPD) is an important indicator of wind as a power source which is usually included in regional wind resource maps as useful prior information to identify potentially attractive sites for the installation of wind projects. In this paper, a comparison is made of eight proposed Measure-Correlate-Predict (MCP) models to estimate the WPDs at a target site. Seven of these models use the Support Vector Regression (SVR) and the eighth the Multiple Linear Regression (MLR) technique, which serves as a basis to compare the performance of the other models. In addition, a wrapper technique with 10-fold cross-validation has been used to select the optimal set of input features for the SVR and MLR models. Some of the eight models were trained to directly estimate the mean hourly WPDs at a target site. Others, however, were firstly trained to estimate the parameters on which the WPD depends (i.e. wind speed and air density) and then, using these parameters, the target site mean hourly WPDs. The explanatory features considered are different combinations of the mean hourly wind speeds, wind directions and air densities recorded in 2014 at ten weather stations in the Canary Archipelago (Spain). The conclusions that can be drawn from the study undertaken include the argument that the most accurate method for the long-term estimation of WPDs requires the execution of a
Childhood hyperactivity/inattention and eating disturbances predict binge eating in adolescence
Sonneville, Kendrin R.; Calzo, Jerel P.; Horton, Nicholas J.; Field, Alison E.; Crosby, Ross D.; Solmi, Francesca; Micali, Nadia
2015-01-01
Background Identifying childhood predictors of binge eating and understanding risk mechanisms could help improve prevention and detection efforts. The aim of this study was to examine whether features of attention deficit-hyperactivity disorder (ADHD), as well as childhood eating disturbances, predicted binge eating later in adolescence. Method We studied specific risk factors for the development of binge eating during mid-adolescence among 7,120 males and females from the Avon Longitudinal Study of Parents and Children (ALSPAC), a cohort study of children in the United Kingdom, using data from multiple informants to develop structural equation models. Repeated assessment of eating disturbances during childhood (mid-childhood overeating, late-childhood overeating, and early-adolescent strong desire for food), as well as teacher and parent reported hyperactivity/inattention during mid- and late-childhood, were considered as possible predictors of mid-adolescent binge eating. Results Prevalence of binge eating during mid-adolescence in our sample was 11.6%. The final model of predictors of binge eating during mid-adolescence included direct effects of late-childhood overeating (standardized estimate: 0.145, 95% CI: 0.038, 0.259; p=0.009) and early-adolescent strong desire for food (standardized estimate: 0.088, 95% CI: −0.002, 0.169; p=0.05). Hyperactivity/inattention during late-childhood indirectly predicted binge eating during mid-adolescence (standardized estimate: 0.085, 95% CI: 0.007, 0.128; p=0.03) via late-childhood overeating and early-adolescent strong desire for food. Conclusions Our findings indicate that early ADHD symptoms, in addition to an overeating phenotype, contribute to risk for adolescent binge eating. These findings lend support to the potential role of hyperactivity/inattention in the development of overeating and binge eating. PMID:26098685
Childhood hyperactivity/inattention and eating disturbances predict binge eating in adolescence.
Sonneville, K R; Calzo, J P; Horton, N J; Field, A E; Crosby, R D; Solmi, F; Micali, N
2015-01-01
Identifying childhood predictors of binge eating and understanding risk mechanisms could help improve prevention and detection efforts. The aim of this study was to examine whether features of attention-deficit/hyperactivity disorder (ADHD), as well as childhood eating disturbances, predicted binge eating later in adolescence. We studied specific risk factors for the development of binge eating during mid-adolescence among 7120 males and females from the Avon Longitudinal Study of Parents and Children (ALSPAC), a cohort study of children in the UK, using data from multiple informants to develop structural equation models. Repeated assessment of eating disturbances during childhood (mid-childhood overeating, late-childhood overeating and early-adolescent strong desire for food), as well as teacher- and parent-reported hyperactivity/inattention during mid- and late childhood, were considered as possible predictors of mid-adolescent binge eating. Prevalence of binge eating during mid-adolescence in our sample was 11.6%. The final model of predictors of binge eating during mid-adolescence included direct effects of late-childhood overeating [standardized estimate 0.145, 95% confidence interval (CI) 0.038–0.259, p = 0.009] and early-adolescent strong desire for food (standardized estimate 0.088, 95% CI −0.002 to 0.169, p = 0.05). Hyperactivity/inattention during late childhood indirectly predicted binge eating during mid-adolescence (standardized estimate 0.085, 95% CI 0.007–0.128, p = 0.03) via late-childhood overeating and early-adolescent strong desire for food. Our findings indicate that early ADHD symptoms, in addition to an overeating phenotype, contribute to risk for adolescent binge eating. These findings lend support to the potential role of hyperactivity/inattention in the development of overeating and binge eating.
Fatigue life prediction and strength degradation of wind turbine rotor blade composites
Nijssen, R.P.L.
2006-01-01
Wind turbine rotor blades are subjected to a large number of highly variable loads, but life predictions are typically based on constant amplitude fatigue behaviour. Therefore, it is important to determine how service life under variable amplitude fatigue can be estimated from constant amplitude
Reconstructing disturbances and their biogeochemical consequences over multiple timescales
McLauchlan, Kendra K.; Higuera, Philip E.; Gavin, Daniel G.; Perakis, Steven S.; Mack, Michelle C.; Alexander, Heather; Battles, John; Biondi, Franco; Buma, Brian; Colombaroli, Daniele; Enders, Sara K.; Engstrom, Daniel R.; Hu, Feng Sheng; Marlon, Jennifer R.; Marshall, John; McGlone, Matt; Morris, Jesse L.; Nave, Lucas E.; Shuman, Bryan; Smithwick, Erica A.H.; Urrego, Dunia H.; Wardle, David A.; Williams, Christopher J.; Williams, Joseph J.
2014-01-01
Ongoing changes in disturbance regimes are predicted to cause acute changes in ecosystem structure and function in the coming decades, but many aspects of these predictions are uncertain. A key challenge is to improve the predictability of postdisturbance biogeochemical trajectories at the ecosystem level. Ecosystem ecologists and paleoecologists have generated complementary data sets about disturbance (type, severity, frequency) and ecosystem response (net primary productivity, nutrient cycling) spanning decadal to millennial timescales. Here, we take the first steps toward a full integration of these data sets by reviewing how disturbances are reconstructed using dendrochronological and sedimentary archives and by summarizing the conceptual frameworks for carbon, nitrogen, and hydrologic responses to disturbances. Key research priorities include further development of paleoecological techniques that reconstruct both disturbances and terrestrial ecosystem dynamics. In addition, mechanistic detail from disturbance experiments, long-term observations, and chronosequences can help increase the understanding of ecosystem resilience.
Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba
2016-05-01
In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Dynamic Loads and Wake Prediction for Large Wind Turbines Based on Free Wake Method
Institute of Scientific and Technical Information of China (English)
Cao Jiufa; Wang Tongguang; Long Hui; Ke Shitang; Xu Bofeng
2015-01-01
With large scale wind turbines ,the issue of aerodynamic elastic response is even more significant on dy-namic behaviour of the system .Unsteady free vortex wake method is proposed to calculate the shape of wake and aerodynamic load .Considering the effect of aerodynamic load ,inertial load and gravity load ,the decoupling dy-namic equations are established by using finite element method in conjunction of the modal method and equations are solved numerically by Newmark approach .Finally ,the numerical simulation of a large scale wind turbine is performed through coupling the free vortex wake modelling with structural modelling .The results show that this coupling model can predict the flexible wind turbine dynamic characteristics effectively and efficiently .Under the influence of the gravitational force ,the dynamic response of flapwise direction contributes to the dynamic behavior of edgewise direction under the operational condition of steady wind speed .The difference in dynamic response be-tween the flexible and rigid wind turbines manifests when the aerodynamics/structure coupling effect is of signifi-cance in both wind turbine design and performance calculation .
International Nuclear Information System (INIS)
Mazaudier, C.
1985-01-01
This paper presents three case studies of ionospheric disturbances in electric fields, currents, and winds during periods of geomagnetic storms. These disturbances are detected by the Saint-Santin incoherent scatter radar. The disturbances are shown to originate from two distinct physical mechanism: (1) penetration of electric fields to lower latitudes during times of rapid change in magnetospheric convection; and (2) the action of the disturbed ionospheric dynamo driven by storm-induced wind disturbances. The storm of June 6, 1978, shows a simple illustration of penetrative convection electric fields. The storm of March 22, 1979, gives additional examples of this effect both when the B/sub Z/ component of the interplanetary fields turns southward and northward. The observed events on March 23 are clearly identifiable as the delayed response of the disturbance ionospheric dynamo
International Nuclear Information System (INIS)
Pedersen, Eja; Persson-Waye, K.
2002-02-01
To evaluate the occurrence of annoyance from wind turbines, a study was performed in Laholm in May 2000. The aim was to obtain dose response relationships between calculated sound levels and noise annoyance and appropriate sound description as well as analysing the influence of other variables on noise annoyance. A questionnaire survey was performed in 6 areas comprising 16 wind turbines, of which 14 had an effect of 600 kW. The purpose of the study was masked. Among questions on living conditions in the countryside, questions directly related to wind turbines were included. The study population (n=518) comprised one randomly selected subject between the ages of 18 to 75 years in each household living within a calculated wind turbine sound level of 25 to 40 dBA. The response rate was 68.7% (n=356). Calculated distributions of A-weighted sound level were performed for each area and plotted on geographical maps in 2.5 dBA steps. Each dwelling could thus be given a sound level within an interval of 2.5 dBA. The most frequently occurring source of noise annoyance was noise from rotor blades. The proportions of respondents annoyed by noise increased with calculated sound level. Among respondents exposed to sound levels of 35.0-37.5 dBA, 43% responded themselves to be rather or much annoyed. A-weighted sound level was only one variable explaining annoyance. Annoyance was correlated to a larger extent by the intrusiveness of the sound character swishing. Noise annoyance was interrelated to the respondents' opinion of the visual impact of wind turbines, while attitude towards wind power in general had no greater influence. Disturbance of spoilt view was reported to a similar degree as noise disturbance. Further investigations are needed to clarify factors of importance for the disturbance of view. All the wind turbines in the study had constant rotation speed. The greater wind turbines that are now erected often have variable speed, which may lead to a sound comprising
Ren, Yaxuan; Zhang, Xu; You, Jianing; Jiang, Yongqiang; Lin, Min-Pei; Leung, Freedom
2017-12-18
Adolescence is a developmental period associated with a heightened risk for suicidal ideation. During this phase of life, individuals tend to focus on both intrapersonal self and interpersonal relationships. Thus, it is of much significance to understand the roles of intrapersonal and interpersonal factors in the development of suicidal ideation among adolescents. The present study examined the reciprocal associations between identity disturbance, relationship disturbance, and suicidal ideation by using a three-wave cross-lag model in a sample of adolescents. A number of 3,600 Chinese adolescents (56.6% females, mean age = 14.58 years) completed questionnaires assessing the three main study variables as well as depressive symptoms, anxiety, and suicidal attempts three times at 6-month intervals. After controlling for gender, age, depressive symptoms, anxiety, and suicidal attempts, relationship disturbance significantly predicted suicidal ideation over time, and vice versa. Suicidal ideation significantly predicted identity disturbance over time, but not vice versa. We also found the mediating effect of relationship disturbance in the path from identity disturbance to suicidal ideation. The results suggested the important role of previous relationship disturbance in predicting later suicidal ideation. Theoretical and clinical implications of these findings were discussed. © 2017 Wiley Periodicals, Inc.
UDE-based control of variable-speed wind turbine systems
Ren, Beibei; Wang, Yeqin; Zhong, Qing-Chang
2017-01-01
In this paper, the control of a PMSG (permanent magnet synchronous generator)-based variable-speed wind turbine system with a back-to-back converter is considered. The uncertainty and disturbance estimator (UDE)-based control approach is applied to the regulation of the DC-link voltage and the control of the RSC (rotor-side converter) and the GSC (grid-side converter). For the rotor-side controller, the UDE-based vector control is developed for the RSC with PMSG control to facilitate the application of the MPPT (maximum power point tracking) algorithm for the maximum wind energy capture. For the grid-side controller, the UDE-based vector control is developed to control the GSC with the power reference generated by a UDE-based DC-link voltage controller. Compared with the conventional vector control, the UDE-based vector control can achieve reliable current decoupling control with fast response. Moreover, the UDE-based DC-link voltage regulation can achieve stable DC-link voltage under model uncertainties and external disturbances, e.g. wind speed variations. The effectiveness of the proposed UDE-based control approach is demonstrated through extensive simulation studies in the presence of coupled dynamics, model uncertainties and external disturbances under varying wind speeds. The UDE-based control is able to generate more energy, e.g. by 5% for the wind profile tested.
Voltage Control in Wind Power Plants with Doubly Fed Generators
DEFF Research Database (Denmark)
Garcia, Jorge Martinez
In this work, the process of designing a wind power plant composed of; doubly fed induction generators, a static compensator unit, mechanically switched capacitors and on-load tap changer, for voltage control is shown. The selected control structure is based on a decentralized system, since...... supplied by the doubly fed induction generator wind turbines is overcome by installing a reactive power compensator, i.e. a static compensator unit, which is coordinated with the plant control by a specific dispatcher. This dispatcher is set according to the result of the wind power plant load flow....... To release the operation of the converters during steady-state disturbances, mechanically switched capacitors are installed in the wind power plant, which due to their characteristics, they are appropriate for permanent disturbances compensation. The mechanically switched capacitors are controlled to allow...
Practical aspects of decentralized wind energy systems
Energy Technology Data Exchange (ETDEWEB)
Beurskens, H J.M.
1982-11-01
Some practical aspects of wind energy systems are described with emphasis on small wind energy conversion systems, both horizontal and vertical axis turbines. Reviewed are the power train of the installation including the speed control and power construction. Power efficiency of small wind turbines available and in operation in the Netherlands is dealt with. Environmental aspects such as noise, disturbance of tv and radio signals, impact on birds and the landscape are mentioned briefly.
Time dependent response of equatorial ionospheric electric fieldsto magnetospheric disturbances
Fejer, Bela G.; Scherliess, L.
1995-01-01
We use extensive radar measurements of F region vertical plasma drifts and auroral electrojet indices to determine the storm time dependence of equatorial zonal electric fields. These disturbance drifts result from the prompt penetration of high latitude electric fields and from the dynamo action of storm time winds which produce largest perturbations a few hours after the onset of magnetic activity. The signatures of the equatorial disturbance electric fields change significantly depending o...
Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system
Manal, Messadi; Adel, Mellit; Karim, Kemih; Malek, Ghanes
2015-01-01
This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. Project supported by the CMEP-TASSILI Project (Grant No. 14MDU920).
Potential health impact of wind turbines
International Nuclear Information System (INIS)
2010-05-01
In response to public health concerns about wind turbines, a study was conducted to review the scientific evidence on the potential health effects of wind turbines. Several research questions were examined, including scientific evidence on the potential health impacts of wind turbines; the relationship between wind turbine noise and health; the relationship between low frequency sound, infrasound and health; assessment of exposure to wind turbines; wind turbine health and safety hazards and Ontario wind turbine setbacks; community consultation prior to wind farm construction and data gaps and research needs. The study showed that although some people living near wind turbines reported symptoms such as dizziness, headaches, and sleep disturbance, the scientific evidence available to date does not demonstrate a direct causal link between wind turbine noise and adverse health effects. The sound level from wind turbines at common residential setbacks is not sufficient to cause hearing impairment or other direct health effects, although some people may find it annoying. 41 refs., 1 appendix.
Spatial mapping and attribution of Wyoming wind turbines, 2012
O'Donnell, Michael S.; Fancher, Tammy S.
2014-01-01
These data represent locations of wind turbines found within Wyoming as of August 2012. We assigned each wind turbine to a wind farm and, in these data, provide information about each turbine’s potential megawatt output, rotor diameter, hub height, rotor height, the status of the land ownership where the turbine exists, the county each turbine is located in, wind farm power capacity, the number of units currently associated with each wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some of the attributes are estimates based on the information we found via the American Wind Energy Association and other on-line reports. The locations are derived from National Agriculture Imagery Program (2009 and 2012) true color aerial photographs and have a positional accuracy of approximately +/-5 meters. These data will provide a planning tool for wildlife- and habitat-related projects underway at the U.S. Geological Survey’s Fort Collins Science Center and other government and non-government organizations. Specifically, we will use these data to support quantifying disturbances of the landscape as related to wind energy as well as to quantify indirect disturbances to flora and fauna. This data set represents an update to a previous version by O’Donnell and Fancher (2010).
Wind Turbine Providing Grid Support
DEFF Research Database (Denmark)
2011-01-01
changing the operation of the wind turbine to a more efficient working point.; When the rotational speed of the rotor reaches a minimum value, the wind turbine enters a recovery period to re-accelerate the rotor to the nominal rotational speed while further contributing to the stability of the electrical......A variable speed wind turbine is arranged to provide additional electrical power to counteract non-periodic disturbances in an electrical grid. A controller monitors events indicating a need to increase the electrical output power from the wind turbine to the electrical grid. The controller...... is arranged to control the wind turbine as follows: after an indicating event has been detected, the wind turbine enters an overproduction period in which the electrical output power is increased, wherein the additional electrical output power is taken from kinetic energy stored in the rotor and without...
Energy Technology Data Exchange (ETDEWEB)
Kassem, Ahmed M. [Beni-Suef University, Electrical Dept., Beni Suef (Egypt)
2012-09-15
This paper investigates the application of the model predictive control (MPC) approach to control the voltage and frequency of a stand alone wind generation system. This scheme consists of a wind turbine which drives an induction generator feeding an isolated load. A static VAR compensator is connected at the induction generator terminals to regulate the load voltage. The rotor speed, and thereby the load frequency are controlled via adjusting the mechanical power input using the blade pitch-angle. The MPC is used to calculate the optimal control actions including system constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional model predictive control (FMPC) is employed. Digital simulations have been carried out in order to validate the effectiveness of the proposed scheme. The proposed controller has been tested through step changes in the wind speed and the load impedance. Simulation results show that adequate performance of the proposed wind energy scheme has been achieved. Moreover, this scheme is robust against the parameters variation and eliminates the influence of modeling and measurement errors. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Pedersen, Eja [Halmstad Univ. (Sweden). School of Business and Engineering
2002-02-01
Wind power generates electricity at low environmental costs, but local residents sometimes have had complains. To support further development of wind farms, it is important to find out if people are annoyed and if so, in what way. This is a preliminary study that will be followed by an extensive survey in Laholm, a municipality in the South of Sweden with 44 wind power turbines. A survey based on cases of complaints in Laholm shows that outdoor noise is the most common annoyance. Others are indoor noise, shadow flicker and visual impact. Residents in one nearby location, Falkenberg, that resembles the landscape in Laholm, were interviewed. The most common source of annoyance was traffic noise. The turbines annoyed no respondent, even thought the estimated noise levels in some cases exceeded the 40-dBA limit. Also in another location outside Halmstad people that lived close to the wind turbines experienced no problems. The number of people actually indicating annoyance by wind turbines is probably fairly small. The most common annoyance is that from wind turbine noise. People who are annoyed of noise could eater be exposed to higher noise levels than estimated or of certain discomforting type of noise. Several other factors of individual nature could also affect the annoyance. These are assumed to be the general attitude towards wind power, if you are in the possession of a turbine, if you are raised in the countryside or in a city, and the general attitude towards the authorities. Following these assumptions, several hypotheses for the main survey are discussed and described.
Wind Turbine Pitch Control and Load Mitigation Using an L1 Adaptive Approach
Directory of Open Access Journals (Sweden)
Danyong Li
2014-01-01
Full Text Available We present an application of L1 adaptive output feedback control design to wind turbine collective pitch control and load mitigation. Our main objective is the design of an L1 output feedback controller without wind speed estimation, ensuring that the generator speed tracks the reference trajectory with robustness to uncertain parameters and time-varying disturbances (mainly the uniform wind disturbance across the wind turbine rotor. The wind turbine model CART (controls advanced research turbine developed by the national renewable energy laboratory (NREL is used to validate the performance of the proposed L1 adaptive controller using the FAST (fatigue, aerodynamics, structures, and turbulence code. A comparative study is also conducted between the proposed controller and the most popular methods in practice: gain scheduling PI (GSPI controls and disturbance accommodating control (DAC methods. The results show better performance of L1 output feedback controller over the other two methods. Moreover, based on the FAST software and LQR analysis in the reference model selection of L1 adaptive controller, tradeoff can be achieved between control performance and loads mitigation.
Uniform stable observer for the disturbance estimation in two renewable energy systems.
Rubio, José de Jesús; Ochoa, Genaro; Balcazar, Ricardo; Pacheco, Jaime
2015-09-01
In this study, an observer for the states and disturbance estimation in two renewable energy systems is introduced. The restrictions of the gains in the proposed observer are found to guarantee its stability and the convergence of its error; furthermore, these results are utilized to obtain a good estimation. The introduced technique is applied for the states and disturbance estimation in a wind turbine and an electric vehicle. The wind turbine has a rotatory tower to catch the incoming air to be transformed in electricity and the electric vehicle has generators connected with its wheels to catch the vehicle movement to be transformed in electricity. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD
DEFF Research Database (Denmark)
Yang, Hua; Shen, Wen Zhong; Xu, Haoran
2014-01-01
Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...
Adaptive State Feedback—Theory and Application for Wind Turbine Control
Directory of Open Access Journals (Sweden)
Kaman Thapa Magar
2017-12-01
Full Text Available A class of adaptive disturbance tracking controllers (ADTCs is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR to ensure stability. In this paper, we show that the ASPR property of a plant is retained with the addition of disturbance and state estimation and state feedback, thereby ensuring the stability of the augmented system. The proposed adaptive controller with augmentation is presented in the context of maximum power extraction from a wind turbine in a low-wind-speed operation region. A simulation and comparative study on the National Renewable Energy Laboratory’s (NREL’s 5 MW nonlinear wind turbine model with an existing baseline Proportional-Integral-Derivative(PID controller shows that the proposed controller is more effective than the existing baseline PID controller.
Energy Technology Data Exchange (ETDEWEB)
Helldin, Jan Olof; Skarin, Anna; Widemo, Fredrik [SLU, Uppsala (Sweden); Jung, Jens [SLU, Skara (Sweden); Neumann, Wiebke [SLU, Umeaa (Sweden); Olsson, Mattias [SLU (Sweden)
2012-06-15
available on wild deer, reindeer and large carnivores during construction work suggest that these animals may temporarily avoid wind farms during this period. However, the data is not conclusive. - Noise emissions from wind turbines can theoretically disturb animal communication, and also visual stimuli (including reflections, shadows and lighting) may annoy or stress both wildlife and livestock. However, the few studies available suggest the lack of such effects, or a swift habituation to the disturbance, and therefore a limited impact. - Animals may also get accustomed to the other disturbances from wind power. For example, both domestic and wild reindeer appear to remain in areas despite human presence, at least when no alternative areas are available. The ability to habituate varies with species, sex, age, individual, time of year, type of disturbance, and how frequent and predictable disturbances are, so overall, habituation cannot be presupposed. - There may be differences in the response to disturbance, depending on landscape and current land use. In already disturbed areas, such as most agricultural landscapes, wind power may not affect the occurring species to the same extent as it would in more sparsely populated forest and mountain areas. - The effects may also depend on the size of the wind farm. At the construction of large wind farms, even small and localised effects may sum up to significant impact, with consequences at the population level. - Our summary highlights the large knowledge gaps in the field and indicates the need for research as well as for efficient environmental monitoring. Of particular need is to study the effects of noise and visual impacts from the turbines. Also studies are needed on the localisation of new wind power in relation to areas of particular value for ungulates and large predators. It is important that the potential cumulative impacts of wind power are considered, as these may lead to consequences at the population level and
M.M. Cowden; J.L. Hart; C.J. Schweitzer; D.C. Dey
2014-01-01
Forest disturbances are discrete events in space and time that disrupt the biophysical environment and impart lasting legacies on forest composition and structure. Disturbances are often classified along a gradient of spatial extent and magnitude that ranges from catastrophic events where most of the overstory is removed to gap-scale events that modify local...
Vibration Analysis and Time Series Prediction for Wind Turbine Gearbox Prognostics
Directory of Open Access Journals (Sweden)
Hossam A. Gabbar
2013-01-01
Full Text Available Premature failure of a gearbox in a wind turbine poses a high risk of increasing the operational and maintenance costs and decreasing the profit margins. Prognostics and health management (PHM techniques are widely used to access the current health condition of the gearbox and project it in future to predict premature failures. This paper proposes such techniques for predicting gearbox health condition index extracted from the vibration signals emanating from the gearbox. The progression of the monitoring index is predicted using two different prediction techniques, adaptive neuro-fuzzy inference system (ANFIS and nonlinear autoregressive model with exogenous inputs (NARX. The proposed prediction techniques are evaluated through sun-spot data-set and applied on vibration based health related monitoring index calculated through psychoacoustic phenomenon. A comparison is given for their prediction accuracy. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating features, the level of damage/degradation, and their progression.
International Nuclear Information System (INIS)
Ghasemian, Masoud; Nejat, Amir
2015-01-01
Operating wind turbines generate tonal and broadband noises affecting the living environment adversely; especially small wind turbines located in the vicinity of human living places. Therefore, it is important to determine the level of noise pollution of such type of wind turbine installation. The current study carries out numerical prediction for aerodynamic noise radiated from an H-Darrieus Vertical Axis Wind Turbine. Incompressible LES (Large Eddy Simulation) is conducted to obtain the instantaneous turbulent flow field. The noise predictions are performed by the Ffowcs Williams and Hawkings (FW–H) acoustic analogy formulation. Simulations are performed for five different tip-speed ratios. First, the mean torque coefficient is compared with the experimental data, and good agreement is observed. Then, the research focuses on the broadband noises of the turbulent boundary layers and the tonal noises due to blade passing frequency. The contribution of the thickness, loading and quadrupole noises are investigated, separately. The results indicate a direct relation between the strength of the radiated noise and the rotational speed. Furthermore, the effect of receiver distance on the OASPL (Overall Sound Pressure Level) is investigated. It is concluded that the OASPL varies with a logarithmic trend with the receiver distance as it was expected. - Highlights: • Large Eddy Simulation has been used to predict the turbulent flow field. • The Ffowcs Williams and Hawkings method was employed to predict radiated noise. • There is a direct relation between the radiated noise and the tip speed ratio. • The quadrupole noises have negligible effect on the tonal noises
Nonlinear Robust Control of a Hypersonic Flight Vehicle Using Fuzzy Disturbance Observer
Directory of Open Access Journals (Sweden)
Lei Zhengdong
2013-01-01
Full Text Available This paper is concerned with a novel tracking controller design for a hypersonic flight vehicle in complex and volatile environment. The attitude control model is challengingly constructed with multivariate uncertainties and external disturbances, such as structure dynamic and stochastic wind disturbance. In order to resist the influence of uncertainties and disturbances on the flight control system, nonlinear disturbance observer is introduced to estimate them. Moreover, for the sake of high accuracy and sensitivity, fuzzy theory is adopted to improve the performance of the nonlinear disturbance observer. After the total disturbance is eliminated by dynamic inversion method, a cascade system is obtained and then stabilized by a sliding-mode controller. Finally, simulation results show that the strong robust controller achieves excellent performance when the closed-loop control system is influenced by mass uncertainties and external disturbances.
International Nuclear Information System (INIS)
Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin
2016-01-01
Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.
Investigation of the possible influence of wind turbines on birds
Energy Technology Data Exchange (ETDEWEB)
Winkelman, J E
1988-11-01
An overview is given of carried out and current field studies, results and gaps with regard to bird damage caused by wind turbines. Present research aims at disturbance of the environment, chances for birds to become victims and actual number of victims. Gaps in our knowledge exist in particular with regard to victims which fall at night. Investigation of the chances for birds to become victims at night is preferable to searching night victims by daylight because of minimal chances of finding them and high labour-intensity. In general it can be said that current field research at the relation between wind turbines and birds is site-oriented. Broader research, especially aimed at the disturbance aspect, is not possible right now, because large wind turbines and wind turbine arrays are rare. 3 figs., 7 refs., 5 tabs.
Pressure integration technique for predicting wind-induced response in high-rise buildings
Directory of Open Access Journals (Sweden)
Aly Mousaad Aly
2013-12-01
Full Text Available This paper presents a procedure for response prediction in high-rise buildings under wind loads. The procedure is illustrated in an application example of a tall building exposed to both cross-wind and along-wind loads. The responses of the building in the lateral directions combined with torsion are estimated simultaneously. Results show good agreement with recent design standards; however, the proposed procedure has the advantages of accounting for complex mode shapes, non-uniform mass distribution, and interference effects from the surrounding. In addition, the technique allows for the contribution of higher modes. For accurate estimation of the acceleration response, it is important to consider not only the first two lateral vibrational modes, but also higher modes. Ignoring the contribution of higher modes may lead to underestimation of the acceleration response; on the other hand, it could result in overestimation of the displacement response. Furthermore, the procedure presented in this study can help decision makers, involved in a tall building design/retrofit to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, damping enhancement, and/or materials change, with an objective to improve the resiliency and the serviceability under extreme wind actions.
Analysis of the wind rose at Itaorna, Brazil
International Nuclear Information System (INIS)
Nicolli, D.
1982-05-01
The Angra-I nuclear power plant is located on the southeastern coast of Brazil, in a bowl-shaped area with hills on three sides and a bay on the fourth side. To the north the surrounding hills rise to more than 600 meters, in the other directions they are lower. At the botton of this area a meteorological mast 50 meters high was installed. Hourly measurements of temperature differences between two levels, as well as wind speed and direction at 50m height were carried out. The wind speed and direction are analysed. The daily air flow at the site shows two distinct characteristics: one nocturnal flow from NE due to the combined effects of the trade and the katabatic winds and a diurnal flow from SW-W generated by the sea breezes. Throughout the year this 'normal' condition is disturbed by low pressure systems that move over the region. For about 10% of the time these weather systems account for the disturbed flow regime in which the winds change direction in a counterclockwise sense. During the day the sea breezes are suppressed by the backing of the winds as well as the trade and katabatic winds during the night. (Author) [pt
Model Predictive Control of Trailing Edge Flaps on a wind turbine blade
DEFF Research Database (Denmark)
Castaignet, Damien; Poulsen, Niels Kjølstad; Buhl, Thomas
2011-01-01
Trailing Edge Flaps on wind turbine blades have been studied in order to achieve fatigue load reduction on the turbine components. We show in this paper how Model Predictive Control can be used to do frequency weighted control of the trailing edge flaps in order to reduce fatigue damage on the bl...
Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs
Institute of Scientific and Technical Information of China (English)
Yi Zhang; Xiangjie Liu; Bin Qu
2017-01-01
Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.
On wake modeling, wind-farm gradients, and AEP predictions at the Anholt wind farm
Directory of Open Access Journals (Sweden)
A. Peña
2018-04-01
Full Text Available We investigate wake effects at the Anholt offshore wind farm in Denmark, which is a farm experiencing strong horizontal wind-speed gradients because of its size and proximity to land. Mesoscale model simulations are used to study the horizontal wind-speed gradients over the wind farm. From analysis of the mesoscale simulations and supervisory control and data acquisition (SCADA, we show that for westerly flow in particular, there is a clear horizontal wind-speed gradient over the wind farm. We also use the mesoscale simulations to derive the undisturbed inflow conditions that are coupled with three commonly used wake models: two engineering approaches (the Park and G. C. Larsen models and a linearized Reynolds-averaged Navier–Stokes approach (Fuga. The effect of the horizontal wind-speed gradient on annual energy production estimates is not found to be critical compared to estimates from both the average undisturbed wind climate of all turbines' positions and the undisturbed wind climate of a position in the middle of the wind farm. However, annual energy production estimates can largely differ when using wind climates at positions that are strongly influenced by the horizontal wind-speed gradient. When looking at westerly flow wake cases, where the impact of the horizontal wind-speed gradient on the power of the undisturbed turbines is largest, the wake models agree with the SCADA fairly well; when looking at a southerly flow case, where the wake losses are highest, the wake models tend to underestimate the wake loss. With the mesoscale-wake model setup, we are also able to estimate the capacity factor of the wind farm rather well when compared to that derived from the SCADA. Finally, we estimate the uncertainty of the wake models by bootstrapping the SCADA. The models tend to underestimate the wake losses (the median relative model error is 8.75 % and the engineering wake models are as uncertain as Fuga. These results are specific for
Effect of fall wind on wind power generation; Furyoku hatsuden ni okeru dashikaze no koka
Energy Technology Data Exchange (ETDEWEB)
Nagai, H [Nihon University, Tokyo (Japan)
1997-11-25
Wind conditions in Arakawa Town, Niigata Prefecture, were surveyed by anemometers and anemoscopes installed at 3 different points, and the data are analyzed to develop the prediction model for investigating possibility of introduction of wind mills there. Outlined herein is power generated by fall wind by comparing predicted power availability with the actual results. In order to investigate possibility of power generation by fall wind, the wind conditions and power availability are simulated using the observed wind condition data. Predicted wind velocity involves a large error at a point where frequency of prevailing wind direction is high, and direction in which average wind velocity is high coincides with direction in which land is slanted at a high slope. Fall wind occurs locally for geographical reasons. Location of the wind mill must be carefully considered, because it is complex, although potentially gives a larger quantity of power. A wind mill of 400kW can produce power of around 600MWh annually, when it is located at the suited site confirmed by the wind condition analysis results. 6 refs., 5 figs., 6 tabs.
Bongers, Frans; Poorter, Lourens; Hawthorne, William D; Sheil, Douglas
2009-08-01
The intermediate disturbance hypothesis (IDH) predicts local species diversity to be maximal at an intermediate level of disturbance. Developed to explain species maintenance and diversity patterns in species-rich ecosystems such as tropical forests, tests of IDH in tropical forest remain scarce, small-scale and contentious. We use an unprecedented large-scale dataset (2504 one-hectare plots and 331,567 trees) to examine whether IDH explains tree diversity variation within wet, moist and dry tropical forests, and we analyse the underlying mechanism by determining responses within functional species groups. We find that disturbance explains more variation in diversity of dry than wet tropical forests. Pioneer species numbers increase with disturbance, shade-tolerant species decrease and intermediate species are indifferent. While diversity indeed peaks at intermediate disturbance levels little variation is explained outside dry forests, and disturbance is less important for species richness patterns in wet tropical rain forests than previously thought.
Directory of Open Access Journals (Sweden)
Dirk Cannon
2017-06-01
Full Text Available State-of-the-art wind power forecasts beyond a few hours ahead rely on global numerical weather prediction models to forecast the future large-scale atmospheric state. Often they provide initial and boundary conditions for nested high resolution simulations. In this paper, both upper and lower bounds on forecast range are identified within which global ensemble forecasts provide skilful information for system-wide wind power applications. An upper bound on forecast range is associated with the limit of predictability, beyond which forecasts have no more skill than predictions based on climatological statistics. A lower bound is defined at the lead time beyond which the resolved uncertainty associated with estimating the future large-scale atmospheric state is larger than the unresolved uncertainty associated with estimating the system-wide wind power response to a given large-scale state.The bounds of skilful ensemble forecast range are quantified for three leading global forecast systems. The power system of Great Britain (GB is used as an example because independent verifying data is available from National Grid. The upper bound defined by forecasts of GB-total wind power generation at a specific point in time is found to be 6–8 days. The lower bound is found to be 1.4–2.4 days. Both bounds depend on the global forecast system and vary seasonally. In addition, forecasts of the probability of an extreme power ramp event were found to possess a shorter limit of predictability (4.5–5.5 days. The upper bound on this forecast range can only be extended by improving the global forecast system (outside the control of most users or by changing the metric used in the probability forecast. Improved downscaling and microscale modelling of the wind farm response may act to decrease the lower bound. The potential gain from such improvements have diminishing returns beyond the short-range (out to around 2 days.
Practical use of offsite atmospheric measurements to enhance profitability of onsite wind prediction
Energy Technology Data Exchange (ETDEWEB)
Collier, Craig [GL Garrad Hassan (Canada)
2011-07-01
This paper presents the use of offsite atmospheric measurements to improve the profitability of onsite wind prediction. There are two common sensitivities used, intraday and interday. Results from US mid-western sites show that the error associated with wind predictions is large but there are possibilities for improvement. Inter- and intraday can be used traditionally to contribute towards NWP bias correction. Intraday alone can be used with machine learning and NWP. These techniques are compared and given in order of ease of use and potential accuracy gains. Some considerations and differences for all three techniques, namely, traditional, data assimilation and machine learning are also detailed. An offsite selection matrix shows how elements like location, geography and telemetry rate in the 3 techniques. The experimental setup for all 3 techniques over a 3-month period is given and the results are presented. It can be concluded that the results from these simple experiments show promise but vary in method and time scale.
Predicting wind-induced vibrations of high-rise buildings using unsteady CFD and modal analysis
Zhang, Yue
2015-01-01
This paper investigates the wind-induced vibration of the CAARC standard tall building model, via unsteady Computational Fluid Dynamics (CFD) and a structural modal analysis. In this numerical procedure, the natural unsteady wind in the atmospheric boundary layer is modeled with an artificial inflow turbulence generation method. Then, the turbulent flow is simulated by the second mode of a Zonal Detached-Eddy Simulation, and a conservative quadrature-projection scheme is adopted to transfer unsteady loads from fluid to structural nodes. The aerodynamic damping that represents the fluid-structure interaction mechanism is determined by empirical functions extracted from wind tunnel experiments. Eventually, the flow solutions and the structural responses in terms of mean and root mean square quantities are compared with experimental measurements, over a wide range of reduced velocities. The significance of turbulent inflow conditions and aeroelastic effects is highlighted. The current methodology provides predictions of good accuracy and can be considered as a preliminary design tool to evaluate the unsteady wind effects on tall buildings.
Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth
2014-01-01
This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... These properties facilitate the design of speed controllers by placement of the closed-loop poles (when constraints are not active) and systematic adaptation towards changes in the operating point. Vibration control of undamped modes is achieved by imposing a certain degree of stability to the closed-loop system....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....
Energy Technology Data Exchange (ETDEWEB)
Martin Wilde, Principal Investigator
2012-12-31
ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational
Short term prediction of the horizontal wind vector within a wake vortex warning system
Energy Technology Data Exchange (ETDEWEB)
Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)
2000-07-14
A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)
Predicting Chronic Climate-Driven Disturbances and Their Mitigation
Energy Technology Data Exchange (ETDEWEB)
McDowell, Nate G.; Michaletz, Sean T.; Bennett, Katrina E.; Solander, Kurt C.; Xu, Chonggang; Maxwell, Reed M.; Middleton, Richard S.
2018-01-01
Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances--including drought, heat, insect outbreaks, and wildfire--are rising as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.
Wind Power Prediction using Ensembles
DEFF Research Database (Denmark)
Giebel, Gregor; Badger, Jake; Landberg, Lars
2005-01-01
offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...
Åkerberg, Ludvig
2017-01-01
The expansion of wind power for electrical energy production has increased in recent years and shows no signs of slowing down. This unpredictable source of energy has contributed to destabilization of the electrical grid causing the energy market prices to vary significantly on a daily basis. For energy producers and consumers to make good investments, methods have been developed to make predictions of wind power production. These methods are often based on machine learning were historical we...
Predicting Disturbance-driven Impacts on Ecosystem Services in Coastal Wetlands
Rajan, S.; Crawford, P.; Kleinhuizen, A.; Mortazavi, B.; Sobecky, P.
2017-12-01
Natural and human-induced disturbances pose significant threats to the health and long-term productivity of Alabama coastal wetlands. As wetlands are a vital state resource, decisions on management, restoration, and remediation require actionable data if socio-economic demands are to be balanced with efforts to sustain these habitats. In 2010, the BP oil spill was a large and severe disturbance that threatened coastal Gulf ecosystem services. The largest marine oil spill to date served to highlight fundamental gaps in our knowledge of oil-induced disturbances and the resiliency and restoration of coastal Alabama wetland functions. To address these gaps, a year-long mesocosm study was conducted to investigate oil-induced effects on (i) plant-microbial interactions, (ii) microbial and plant biodiversity, and, (iii) the contributions of microbial genetic biodiversity to ecosystems services. In this study, Avicennia germinans (black mangrove), a C3 plant that grows from the tropics to warm temperate latitudes, were grown with or without mono- and polyculture mixtures of Spartina alterniflora, a C4 plant. At an interval of 3-months, oil was introduced as a pulse disturbance to achieve a concentration of 4000 ppm. Molecular-based analyses of microbial community biodiversity, genetic diversity, and functional metabolic genes were compared to controls (i.e., no oil disturbance). To assess the oil-induced effects on the nitrogen (N) cycle, measurements of denitrification and N fixation processes were conducted. Our results showed that community diversity and phylogenetic diversity significantly changed and that the oil disturbance contributed to the creation of niches for distinct microbial types. The abundance of N-fixing microbial types increased as the abundance of denitrifying microbial types decreased as a result of the oil disturbance. As denitrification is an ecosystem service that directly contributes to removing nitrate (NO3-) loading to coastal zones, impairment
Increasing the competitiveness of wind energy. New technologies for advanced wind predictability
International Nuclear Information System (INIS)
Bertolotti, Fabio
2013-01-01
The performance of thermal and nuclear power plants is assessed routinely and precisely, whereas the performance assessment of wind turbines is lagging far behind. This increases operational costs, reduces energy capture, and makes wind energy less competitive. The paper presents a technology and system with improved 24-h power forecasting, as well as condition monitoring of the rotor blades. The system can be employed by any wind power plant and offers potentials to increase the competitiveness of the power industry. (orig.)
A LIDAR-assisted model predictive controller added on a traditional wind turbine controller
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Hansen, Morten Hartvig
2016-01-01
control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...
Wakes behind wind turbines. Studies on tip vortex evolution and stability
Energy Technology Data Exchange (ETDEWEB)
Odemark, Ylva
2012-07-01
The increased fatigue loads and decreased power output of a wind turbine placed in the wake of another turbine is a well-known problem when building new wind power farms. In order to better estimate the total power output of a wind power farm, knowledge about the development and stability of wind turbine wakes is crucial. In the present thesis, the wake behind a small-scale model turbine was investigated experimentally in a wind tunnel. The velocity in the wake was measured with hot-wire anemometry, for different free stream velocities and tip speed ratios. To characterize the behaviour of the model turbine, the power output, thrust force and rotational frequency of the model were also measured. These results were then compared to calculations using the Blade Element Momentum (BEM) method. New turbine blades for the model was constructed using the same method, in order to get an estimate of the distribution of the lift and drag forces along the blades. This information is needed for comparisons with certain numerical simulations, which however remains to be performed.By placing the turbine at different heights in a turbulent boundary layer, the effects of forest turbulence on wind turbine outputs (power and thrust) could also be investigated.The evolution of the tip vortices shed from the turbine blades was studied by performing velocity measurements around the location of the tip vortex breakdown. The vortices' receptivity to disturbances was then studied by introducing a disturbance in the form of two pulsed jets, located in the rear part of the nacelle. In order to introduce a well-defined disturbance and perform phase-locked measurements, a new experimental setup was constructed and successfully tested for two different disturbance frequencies. The mean stream wise velocity and the stream wise turbulence intensity was found to scale well with the free stream velocity and the spreading of the wake was found to be proportional to the square root of the
International Nuclear Information System (INIS)
Dassen, T.; Parchen, R.; Guidati, G.; Wagner, S.; Kang, S.; Khodak, A.E.
1998-01-01
In the ongoing JOULE-III project 'Development of Design Tools for Reduced Aerodynamic Noise Wind Turbines (DRAW)', prediction codes for inflow-turbulence (IT) noise and turbulent boundary layer trailing-edge (TE) noise, are developed and validated. It is shown that the differences in IT noise radiation between airfoils having a different shape, are correctly predicted. The first, preliminary comparison made between predicted and measured TE noise spectra yields satisfactory results. 17 refs
Aerodynamic Aspects of Wind Energy Conversion
DEFF Research Database (Denmark)
Sørensen, Jens Nørkær
2011-01-01
This article reviews the most important aerodynamic research topics in the field of wind energy. Wind turbine aerodynamics concerns the modeling and prediction of aerodynamic forces, such as performance predictions of wind farms, and the design of specific parts of wind turbines, such as rotor...
Wind resource modelling for micro-siting - Validation at a 60-MW wind farm site
Energy Technology Data Exchange (ETDEWEB)
Hansen, J C; Gylling Mortensen, N [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Said, U S [New and Renewable Energy Authority, Cairo (Egypt)
1999-03-01
This paper investigates and validates the applicability of the WAsP-model for layout optimization and micro-siting of wind turbines at a given site for a 60-MW wind farm at Zafarana at the Gulf of Suez in Egypt. Previous investigations show large gradients in the wind climate within the area. For the design and optimization of the wind farm it was found necessary to verify the WAsP extrapolation of wind atlas results from 2 existing meteorological masts located 5 and 10 km, respectively, from the wind farm site. On-site measurements at the 3.5 x 3.5 km{sup 2} wind farm site in combination with 7 years of near-site wind atlas measurements offer significant amounts of data for verification of wind conditions for micro-siting. Wind speeds, wind directions, turbulence intensities and guests in 47.5 m a.g.l. have been measured at 9 locations across the site. Additionally, one of the site masts is equipped as a reference mast, measuring both vertical profiles of wind speed and temperature as well as air pressure and temperature. The exercise is further facilitated by the fact that winds are highly uni-directional; the north direction accounting for 80-90% of the wind resource. The paper presents comparisons of 5 months of on-site measurements and modeled predictions from 2 existing meteorological masts located at distances of 5 and 10 km, respectively, from the wind farm site. Predictions based on terrain descriptions of the Wind Atlas for the Gulf of Suez 1991-95 showed over-predictions of wind speeds of 4-10%. With calibrated terrain descriptions, made based on measured data and a re-visit to critical parts of the terrain, the average prediction error of wind speeds was reduced to about 1%. These deviations are smaller than generally expected for such wind resource modeling, clearly documenting the validity of using WAsP modeling for micro-siting and layout optimization of the wind farm. (au)
Where eagles nest, the wind also blows: consolidating habitat and energy needs
Tack, J.; Wilson, Jim
2012-01-01
Energy development is rapidly escalating in resource-rich Wyoming, and with it the risks posed to raptor populations. These risks are of increasing concern to the U.S. Fish and Wildlife Service, which is responsible for protecting the persistence of protected species, including raptors. In support of a Federal mandate to protect trust species and the wind energy industry’s need to find suitable sites on which to build wind farms, scientists at the USGS Fort Collins Science Center (FORT) and their partners are conducting research to help reduce impacts to raptor species from wind energy operations. Potential impacts include collision with the turbine blades and habitat disruption and disturbance from construction and operations. This feature describes a science-based tool—a quantitative predictive model—being developed and tested by FORT scientists to potentially avoid or reduce such impacts. This tool will provide industry and resource managers with the biological basis for decisions related to sustainably siting wind turbines in a way that also conserves important habitats for nesting golden eagles. Because of the availability of comprehensive data on nesting sites, golden eagles in Wyoming are the prototype species (and location) for the first phase of this investigation.
Anthropogenic halo disturbances alter landscape and plant richness: a ripple effect.
Liu, Bingliang; Su, Jinbao; Chen, Jianwei; Cui, Guofa; Ma, Jianzhang
2013-01-01
Although anthropogenic landscape fragmentation is often considered as the primary threat to biodiversity, other factors such as immediate human disturbances may also simultaneously threaten species persistence in various ways. In this paper, we introduce a conceptual framework applied to recreation landscapes (RLs), with an aim to provide insight into the composite influences of landscape alteration accompanying immediate human disturbances on plant richness dynamics. These impacts largely occur at patch-edges. They can not only alter patch-edge structure and environment, but also permeate into surrounding natural matrices/patches affecting species persistence-here we term these "Halo disturbance effects" (HDEs). We categorized species into groups based on seed or pollen dispersal mode (animal- vs. wind-dispersed) as they can be associated with species richness dynamics. We evaluated the richness of the two groups and total species in our experimental landscapes by considering the distance from patch-edge, the size of RLs and the intensity of human use over a six-year period. Our results show that animal-dispersed species decreased considerably, whereas wind-dispersed species increased while their richness presented diverse dynamics at different distances from patch-edges. Our findings clearly demonstrate that anthropogenic HDEs produce ripple effects on plant, providing an experimental interpretation for the diverse responses of species to anthropogenic disturbances. This study highlights the importance of incorporating these composite threats into conservation and management strategies.
Anthropogenic halo disturbances alter landscape and plant richness: a ripple effect.
Directory of Open Access Journals (Sweden)
Bingliang Liu
Full Text Available Although anthropogenic landscape fragmentation is often considered as the primary threat to biodiversity, other factors such as immediate human disturbances may also simultaneously threaten species persistence in various ways. In this paper, we introduce a conceptual framework applied to recreation landscapes (RLs, with an aim to provide insight into the composite influences of landscape alteration accompanying immediate human disturbances on plant richness dynamics. These impacts largely occur at patch-edges. They can not only alter patch-edge structure and environment, but also permeate into surrounding natural matrices/patches affecting species persistence-here we term these "Halo disturbance effects" (HDEs. We categorized species into groups based on seed or pollen dispersal mode (animal- vs. wind-dispersed as they can be associated with species richness dynamics. We evaluated the richness of the two groups and total species in our experimental landscapes by considering the distance from patch-edge, the size of RLs and the intensity of human use over a six-year period. Our results show that animal-dispersed species decreased considerably, whereas wind-dispersed species increased while their richness presented diverse dynamics at different distances from patch-edges. Our findings clearly demonstrate that anthropogenic HDEs produce ripple effects on plant, providing an experimental interpretation for the diverse responses of species to anthropogenic disturbances. This study highlights the importance of incorporating these composite threats into conservation and management strategies.
Silva, Carmen; Cabral, João Alexandre; Hughes, Samantha Jane; Santos, Mário
2017-03-01
Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures. Copyright © 2016 Elsevier B.V. All rights reserved.
The new IEA Wind Task 36 on Wind Power Forecasting
DEFF Research Database (Denmark)
Giebel, Gregor; Cline, Joel; Frank, Helmut
Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind E...... forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions....
DEFF Research Database (Denmark)
Pedersen, Mads M.; Larsen, Torben J.; Madsen, Helge Aa
2017-01-01
In this paper an alternative method to evaluate power performance and loads on wind turbines using a blade-mounted flow sensor is investigated. The hypothesis is that the wind speed measured at the blades has a high correlation with the power and loads such that a power or load assessment can...... be performed from a few hours or days of measurements. In the present study a blade-mounted five-hole pitot tube is used as the flow sensor as an alternative to the conventional approach, where the reference wind speed is either measured at a nearby met mast or on the nacelle using lidar technology or cup...... anemometers. From the flow sensor measurements, an accurate estimate of the wind speed at the rotor plane can be obtained. This wind speed is disturbed by the presence of the wind turbine, and it is therefore different from the free-flow wind speed. However, the recorded wind speed has a high correlation...
Wind noise under a pine tree canopy.
Raspet, Richard; Webster, Jeremy
2015-02-01
It is well known that infrasonic wind noise levels are lower for arrays placed in forests and under vegetation than for those in open areas. In this research, the wind noise levels, turbulence spectra, and wind velocity profiles are measured in a pine forest. A prediction of the wind noise spectra from the measured meteorological parameters is developed based on recent research on wind noise above a flat plane. The resulting wind noise spectrum is the sum of the low frequency wind noise generated by the turbulence-shear interaction near and above the tops of the trees and higher frequency wind noise generated by the turbulence-turbulence interaction near the ground within the tree layer. The convection velocity of the low frequency wind noise corresponds to the wind speed above the trees while the measurements showed that the wind noise generated by the turbulence-turbulence interaction is near stationary and is generated by the slow moving turbulence adjacent to the ground. Comparison of the predicted wind noise spectrum with the measured wind noise spectrum shows good agreement for four measurement sets. The prediction can be applied to meteorological estimates to predict the wind noise under other pine forests.
Studies of African wave disturbances with the GISS GCM
Druyan, Leonard M.; Hall, Timothy M.
1994-01-01
Simulations made with the general circulation model of the NASA/Goddard Institute for Space Studies (GISS GCM) run at 4 deg latitude by 5 deg longitude horizontal resolution are analyzed to determine the model's representation of African wave disturbances. Waves detected in the model's lower troposphere over northern Africa during the summer monsoon season exhibit realistic wavelengths of about 2200 km. However, power spectra of the meridional wind show that the waves propagate westward too slowly, with periods of 5-10 days, about twice the observed values. This sluggishness is most pronounced during August, consistent with simulated 600-mb zonal winds that are only about half the observed speeds of the midtropospheric jet. The modeled wave amplitudes are strongest over West Africa during the first half of the summer but decrease dramatically by September, contrary to observational evidence. Maximum amplitudes occur at realistic latitudes, 12 deg - 20 deg N, but not as observed near the Atlantic coast. Spectral analyses suggest some wave modulation of precipitation in the 5-8 day band, and compositing shows that precipitation is slightly enhanced east of the wave trough, coincident with southerly winds. Extrema of low-level convergence west of the wave troughs, coinciding with northerly winds, were not preferred areas for simulated precipitation, probably because of the drying effect of this advection, as waves were generally north of the humid zone. The documentation of African wave disturbances in the GISS GCM is a first step toward considering wave influences in future GCM studies of Sahel drought.
International Nuclear Information System (INIS)
Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin
2016-01-01
The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)
Operation and control of large wind turbines and wind farms
Energy Technology Data Exchange (ETDEWEB)
Soerensen, Poul; Hansen, Anca D.; Thomsen, Kenneth (and others)
2005-09-01
This report is the final report of a Danish research project 'Operation and control of large wind turbines and wind farms'. The objective of the project has been to analyse and assess operational strategies and possibilities for control of different types of wind turbines and different wind farm concepts. The potentials of optimising the lifetime/energy production ratio by means of using revised operational strategies for the individual wind turbines are investigated. Different strategies have been simulated, where the power production is decreased to an optimum when taking loads and actual price of produced electricity into account. Dynamic models and control strategies for the wind farms have also been developed, with the aim to optimise the operation of the wind farms considering participation in power system control of power (frequency) and reactive power (voltage), maximise power production, keep good power quality and limit mechanical loads and life time consumption. The project developed models for 3 different concepts for wind farms. Two of the concepts use active stall controlled wind turbines, one with AC connection and one with modern HVDC/VSC connection of the wind farm. The third concept is based on pitch controlled wind turbines using doubly fed induction generators. The models were applied to simulate the behaviour of the wind farm control when they were connected to a strong grid, and some initial simulations were performed to study the behaviour of the wind farms when it was isolated from the main grid on a local grid. Also the possibility to use the available information from the wind turbine controllers to predict the wind speed has been investigated. The main idea has been to predict the wind speed at a wind turbine using up-wind measurements of the wind speed in another wind turbine. (au)
Energy Technology Data Exchange (ETDEWEB)
Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.
2013-10-01
Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.
Directory of Open Access Journals (Sweden)
Kenneth A. Anyomi
2017-06-01
Full Text Available In Boreal North America, management approaches inspired by the variability in natural disturbances are expected to produce more resilient forests. Wind storms are recurrent within Boreal Ontario. The objective of this study was to simulate wind damage for common Boreal forest types for regular as well as extreme wind speeds. The ForestGALES_BC windthrow prediction model was used for these simulations. Input tree-level data were derived from permanent sample plot (PSP data provided by the Ontario Ministry of Natural Resources. PSPs were assigned to one of nine stand types: Balsam fir-, Jack pine-, Black spruce-, and hardwood-dominated stands, and, Jack pine-, spruce-, conifer-, hardwood-, and Red and White pine-mixed species stands. Morphological and biomechanical parameters for the major tree species were obtained from the literature. At 5 m/s, predicted windthrow ranged from 0 to 20%, with damage increasing to 2 to 90% for winds of 20 m/s and to 10 to 100% for winds of 40 m/s. Windthrow varied by forest stand type, with lower vulnerability within hardwoods. This is the first study to provide such broad simulations of windthrow vulnerability data for Boreal North America, and we believe this will benefit policy decisions regarding risk management and forest planning.
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai
2016-01-01
This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...
Energy Technology Data Exchange (ETDEWEB)
Hong Junjie, E-mail: hongjjie@mail.sysu.edu.cn [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China); Li Liyi, E-mail: liliyi@hit.edu.cn [Dept. Electrical Engineering, Harbin Institute of Technology, Harbin 150000 (China); Zong Zhijian; Liu Zhongtu [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China)
2011-10-15
Highlights: {yields} The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. {yields} A new current control method CEVPC is employed in this motor. {yields} The sectional power supply method is different to the others and effective. {yields} The performance gets worse with voltage and current limitations. - Abstract: To include features such as greater thrust density, higher efficiency without reducing the thrust stability, this paper proposes a section winding permanent magnet linear synchronous motor (SW-PMLSM), whose iron core is continuous, whereas winding is divided. The discrete system model of the motor is derived. With the definition of the current error vector and selection of the value function, the theory of the current error vector based prediction control (CEVPC) for the motor currents is explained clearly. According to the winding section feature, the motion region of the mover is divided into five zones, in which the implementation of the current predictive control method is proposed. Finally, the experimental platform is constructed and experiments are carried out. The results show: the current control effect has good dynamic response, and the thrust on the mover remains constant basically.
Sleep Disturbance During Smoking Cessation: Withdrawal or Side Effect of Treatment?
Ashare, Rebecca L; Lerman, Caryn; Tyndale, Rachel F; Hawk, Larry W; George, Tony P; Cinciripini, Paul; Schnoll, Robert A
2017-06-01
The nicotine-metabolite ratio (NMR) predicts treatment response and is related to treatment side effect severity. Sleep disturbance may be one important side effect, but understanding sleep disturbance effects on smoking cessation is complicated by the fact that nicotine withdrawal also produces sleep disturbance. To evaluate the effects of withdrawal and treatment side effects on sleep disturbance. This is a secondary analysis of data from a clinical trial (Lerman et al., 2015) of 1,136 smokers randomised to placebo ( n = 363), transdermal nicotine (TN; n = 381), or varenicline ( n = 392) and stratified based on NMR (559 slow metabolisers; 577 normal metabolisers). Sleep disturbance was assessed at baseline and at 1-week following the target quit date (TQD). We also examined whether sleep disturbance predicted 7-day point-prevalence abstinence at end-of-treatment (EOT). The varenicline and TN groups exhibited greater increases in sleep disturbance (vs. placebo; treatment × time interaction; p = 0.005), particularly among those who quit smoking at 1-week post-TQD. There was a main effect of NMR ( p = 0.04), but no interactions with treatment. TN and varenicline attenuated withdrawal symptoms unrelated to sleep (vs. placebo). Greater baseline sleep disturbance predicted relapse at EOT ( p = 0.004). Existing treatments may not mitigate withdrawal-related sleep disturbance and adjunctive treatments that target sleep disturbance may improve abstinence rates.
International Nuclear Information System (INIS)
Rideout, K.; Copes, R.; Bos, C.
2010-01-01
This document summarized the potential health hazards associated with wind turbines, such as noise and low frequency sound, vibration and infrasound; electromagnetic fields (EMF); shadow flicker; and ice throw and structural failure. Various symptoms can be attributed to wind turbines, including dizziness, sleep disruption, and headaches. A review of available research regarding potential health affects to residents living in close proximity to wind turbines showed that the sound level associated with wind turbines at common residential setbacks is not sufficient to damage hearing, but may lead to annoyance and sleep disturbance. Research has shown that wind turbines are not a significant source of EMF exposure, and although shadows caused by the blades may be annoying, they are not likely to cause epileptic seizures at normal operational speeds. The risk of injury from ice throw can be minimized with setbacks of 200 to 400 m. Examples of Canadian wind turbine setback guidelines and regulations were also offered. It was concluded that setbacks and operational guidelines can be utilized in combination to address safety hazards, sound levels, land use issues, and impacts on people. 46 refs., 2 tabs., 2 figs.
International Nuclear Information System (INIS)
2002-01-01
The Norwegian government's ambition of developing 3 TWh wind power by 2010 seems hard to fulfill. Recently Norway's first wind park was officially opened on the island of Smoela, just off Kristiansund. The 20 large windmills are Danish-made and described in some detail in this article. Fulfillment of the government's ambition requires that 20 similar power stations are put into operation the coming eight years, and so far it has not been decided to build the next one. Statkraft have great ambitions for wind power. However, environmental considerations present difficulties. For instance, for Smoela, Statkraft spent an extra 4 million NOK on ground cables the last 1.5 km to land in order to minimize the disturbance of bird populations. Considerations for the white-tailed eagle may be a decisive factor in the development of wind power plants in Norway
Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas
2015-09-01
Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.
Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm
DEFF Research Database (Denmark)
Barthelmie, Rebecca Jane; Jensen, L.E.
2010-01-01
Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine...... thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can...... be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under-estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due...
Cross-winds effect on the performance of natural draft wet cooling towers
Energy Technology Data Exchange (ETDEWEB)
Al-Waked, R. [Dhofar Univ., Mechanical Engineering Dept., College of Engineering, Sultanate of Oman (Oman)
2010-01-15
Effects of cross-winds on the thermal performance of natural draft wet cooling towers (NDWCTs) have been investigated. A three-dimensional CFD model has been used to determine the effect of cross-winds on NDWCTs performance surrounded by power plant building structures. The three-dimensional CFD model has utilized the standard k-{epsilon} turbulence model as the turbulence closure. Two cases have been investigated: a stand-alone NDWCT and two NDWCTs within a proposed power plant structures (PPS). It has been found that regardless of the cross-winds direction, an increase of 1.3 k or more could be predicted at cross-winds speeds greater than 4 m/s. Furthermore, the performance of NDWCTs under cross-winds has been found to be dependent on the three major factors: the structure of the approaching cross-winds and whether it is disturbed or undisturbed, the location of the NDWCT in the wake of the other NDWCT, and the location of the NDWCT in front of/in the wake of the PPS. When comparing results from the stand-alone and from the NDWCTs within PPS simulations, differences in {delta}T{sub wo} were found to be less than 1 K for the whole span of cross-winds speeds and could be decreased to 0.7 K for speeds less than 8 m/s. Finally, results obtained from the simulation of a stand-alone NDWCT could be used instead of those from NDWCTs within PPS at a certain cross-winds direction for qualitative comparisons. (authors)
Cross-winds effect on the performance of natural draft wet cooling towers
International Nuclear Information System (INIS)
Al-Waked, R.
2010-01-01
Effects of cross-winds on the thermal performance of natural draft wet cooling towers (NDWCTs) have been investigated. A three-dimensional CFD model has been used to determine the effect of cross-winds on NDWCTs performance surrounded by power plant building structures. The three-dimensional CFD model has utilized the standard k-ε turbulence model as the turbulence closure. Two cases have been investigated: a stand-alone NDWCT and two NDWCTs within a proposed power plant structures (PPS). It has been found that regardless of the cross-winds direction, an increase of 1.3 k or more could be predicted at cross-winds speeds greater than 4 m/s. Furthermore, the performance of NDWCTs under cross-winds has been found to be dependent on the three major factors: the structure of the approaching cross-winds and whether it is disturbed or undisturbed, the location of the NDWCT in the wake of the other NDWCT, and the location of the NDWCT in front of/in the wake of the PPS. When comparing results from the stand-alone and from the NDWCTs within PPS simulations, differences in ΔT wo were found to be less than 1 K for the whole span of cross-winds speeds and could be decreased to 0.7 K for speeds less than 8 m/s. Finally, results obtained from the simulation of a stand-alone NDWCT could be used instead of those from NDWCTs within PPS at a certain cross-winds direction for qualitative comparisons. (authors)
Wind loads on flat plate photovoltaic array fields (nonsteady winds)
Miller, R. D.; Zimmerman, D. K.
1981-01-01
Techniques to predict the dynamic response and the structural dynamic loads of flat plate photovoltaic arrays due to wind turbulence were analyzed. Guidelines for use in predicting the turbulent portion of the wind loading on future similar arrays are presented. The dynamic response and the loads dynamic magnification factor of the two array configurations are similar. The magnification factors at a mid chord and outer chord location on the array illustrated and at four points on the chord are shown. The wind tunnel test experimental rms pressure coefficient on which magnification factors are based is shown. It is found that the largest response and dynamic magnification factor occur at a mid chord location on an array and near the trailing edge. A technique employing these magnification factors and the wind tunnel test rms fluctuating pressure coefficients to calculate design pressure loads due to wind turbulence is presented.
Predicting Faults in Wind Turbines Using SCADA Data
DEFF Research Database (Denmark)
Borchersen, Anders Bech; Larsen, Jesper Abildgaard; Stoustrup, Jakob
2013-01-01
The cost of operation and maintenance of wind turbines is a significant part of the overall cost of wind turbines. To reduce this cost a method for enabling early fault detection is proposed and tested in this paper. The method is taking advantage of the fact that wind turbines in wind farms...... and tested on historical Supervisory Control And Data Acquisition (SCADA) data from nine operational turbines over a testing period of nine months. The performance of the fault detection is found to be acceptable based on the testing period. During the testing period several gear related services were...
Gruber, Karin; Serafin, Stefano; Grubišić, Vanda; Dorninger, Manfred; Zauner, Rudolf; Fink, Martin
2014-05-01
, considering the frequency of wind speed between cut-in and cut-out speed and of winds with a low vertical velocity component only. Wind turbines do not turn on at wind speeds below cut-in speed. Wind turbines are taken off from the generator in the case of wind speeds higher than cut-out speed and inclination angles of the wind vector greater than 8o. All of these parameters were computed at each model grid point in the innermost domain in order to map their spatial variability. The results show that in complex terrain the annual mean wind speed at hub height is not sufficient to predict the capacity factor of a turbine; vertical wind speed and the frequency of horizontal wind speed out of the range of cut-in and cut-out speed contribute substantially to a reduction of the energy harvest and locally high turbulence may considerably raise the building costs.
Short-term load and wind power forecasting using neural network-based prediction intervals.
Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas
2014-02-01
Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.
A Bayesian Belief Network Approach to Predict Damages Caused by Disturbance Agents
Directory of Open Access Journals (Sweden)
Alfred Radl
2017-12-01
Full Text Available In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L. Karst. forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model.
The state-of-the-art in short-term prediction of wind power. A literature overview
Energy Technology Data Exchange (ETDEWEB)
Giebel, G.; Brownsword, R.; Kariniotakis, G.
2003-08-01
Based on an appropriate questionnaire (WP1.1) and some other works already in progress, this report details the state-of-the-art in short term prediction of wind power, mostly summarising nearly all existing literature on the topic. (au)
DEFF Research Database (Denmark)
Lundtang Petersen, Erik; Mortensen, Niels Gylling; Landberg, Lars
Wind power meteorology has evolved as an applied science, firmly founded on boundary-layer meteorology, but with strong links to climatology and geography. It concerns itself with three main areas: siting of wind turbines, regional wind resource assessment, and short-term prediction of the wind...... resource. The history, status and perspectives of wind power meteorology are presented, with emphasis on physical considerations and on its practical application. Following a global view of the wind resource, the elements of boundary layer meteorology which are most important for wind energy are reviewed......: wind profiles and shear, turbulence and gust, and extreme winds. The data used in wind power meteorology stem mainly from three sources: onsite wind measurements, the synoptic networks, and the re-analysis projects. Wind climate analysis, wind resource estimation and siting further require a detailed...
Ice Accretion on Wind Turbine Blades
DEFF Research Database (Denmark)
Hudecz, Adriána; Koss, Holger; Hansen, Martin Otto Laver
2013-01-01
In this paper, both experimental and numerical simulations of the effects of ice accretion on a NACA 64-618 airfoil section with 7° angle of attack are presented. The wind tunnel tests were conducted in a closed-circuit climatic wind tunnel at Force Technology in Denmark. The changes of aerodynamic...... forces were monitored as ice was building up on the airfoil for glaze, rime and mixed ice. In the first part of the numerical analysis, the resulted ice profiles of the wind tunnel tests were compared to profiles estimated by using the 2D ice accretion code TURBICE. In the second part, Ansys Fluent...... of the rime iced ice profile follows the streamlines quite well, disturbing the flow the least. The TURBICE analysis agrees fairly with the profiles produced during the wind tunnel testing....
Baker, N. L.; Tsu, J.; Swadley, S. D.
2017-12-01
We assess the impact of assimilation of CYclone Global Navigation Satellite System (CYGNSS) ocean surface winds observations into the NAVGEM[i] global and COAMPS®[ii] mesoscale numerical weather prediction (NWP) systems. Both NAVGEM and COAMPS® used the NRL 4DVar assimilation system NAVDAS-AR[iii]. Long term monitoring of the NAVGEM Forecast Sensitivity Observation Impact (FSOI) indicates that the forecast error reduction for ocean surface wind vectors (ASCAT and WindSat) are significantly larger than for SSMIS wind speed observations. These differences are larger than can be explained by simply two pieces of information (for wind vectors) versus one (wind speed). To help understand these results, we conducted a series of Observing System Experiments (OSEs) to compare the assimilation of ASCAT wind vectors with the equivalent (computed) ASCAT wind speed observations. We found that wind vector assimilation was typically 3 times more effective at reducing the NAVGEM forecast error, with a higher percentage of beneficial observations. These results suggested that 4DVar, in the absence of an additional nonlinear outer loop, has limited ability to modify the analysis wind direction. We examined several strategies for assimilating CYGNSS ocean surface wind speed observations. In the first approach, we assimilated CYGNSS as wind speed observations, following the same methodology used for SSMIS winds. The next two approaches converted CYGNSS wind speed to wind vectors, using NAVGEM sea level pressure fields (following Holton, 1979), and using NAVGEM 10-m wind fields with the AER Variational Analysis Method. Finally, we compared these methods to CYGNSS wind speed assimilation using multiple outer loops with NAVGEM Hybrid 4DVar. Results support the earlier studies suggesting that NAVDAS-AR wind speed assimilation is sub-optimal. We present detailed results from multi-month NAVGEM assimilation runs along with case studies using COAMPS®. Comparisons include the fit of
Energy Technology Data Exchange (ETDEWEB)
Kim, Bum Suk; Kim, Mann Eung [Korean Register of Shipping, Daejeon (Korea, Republic of); Lee, Young Ho [Korea Maritime Univ., Busan (Korea, Republic of)
2008-07-15
Despite of the laminar-turbulent transition region co-exist with fully turbulence region around the leading edge of an airfoil, still lots of researchers apply to fully turbulence models to predict aerodynamic characteristics. It is well known that fully turbulent model such as standard k-model couldn't predict the complex stall and the separation behavior on an airfoil accurately, it usually leads to over prediction of the aerodynamic characteristics such as lift and drag forces. So, we apply correlation based transition model to predict aerodynamic performance of the NREL (National Renewable Energy Laboratory) Phase IV wind turbine. And also, compare the computed results from transition model with experimental measurement and fully turbulence results. Results are presented for a range of wind speed, for a NREL Phase IV wind turbine rotor. Low speed shaft torque, power, root bending moment, aerodynamic coefficients of 2D airfoil and several flow field figures results included in this study. As a result, the low speed shaft torque predicted by transitional turbulence model is very good agree with the experimental measurement in whole operating conditions but fully turbulent model(K- {epsilon}) over predict the shaft torque after 7m/s. Root bending moment is also good agreement between the prediction and experiments for most of the operating conditions, especially with the transition model.
International Nuclear Information System (INIS)
Kim, Bum Suk; Kim, Mann Eung; Lee, Young Ho
2008-01-01
Despite of the laminar-turbulent transition region co-exist with fully turbulence region around the leading edge of an airfoil, still lots of researchers apply to fully turbulence models to predict aerodynamic characteristics. It is well known that fully turbulent model such as standard k-model couldn't predict the complex stall and the separation behavior on an airfoil accurately, it usually leads to over prediction of the aerodynamic characteristics such as lift and drag forces. So, we apply correlation based transition model to predict aerodynamic performance of the NREL (National Renewable Energy Laboratory) Phase IV wind turbine. And also, compare the computed results from transition model with experimental measurement and fully turbulence results. Results are presented for a range of wind speed, for a NREL Phase IV wind turbine rotor. Low speed shaft torque, power, root bending moment, aerodynamic coefficients of 2D airfoil and several flow field figures results included in this study. As a result, the low speed shaft torque predicted by transitional turbulence model is very good agree with the experimental measurement in whole operating conditions but fully turbulent model(K- ε) over predict the shaft torque after 7m/s. Root bending moment is also good agreement between the prediction and experiments for most of the operating conditions, especially with the transition model
Energy Technology Data Exchange (ETDEWEB)
Rydell, Jens; Hedenstroem, Anders; Green, Martin
2011-07-01
Full text: The noctule bat Nyctalus noctula is apparently the species most seriously affected by wind turbine mortality in northern Europe. It occurs in south Sweden up to about 60oN, although the abundance is much higher in lowland agricultural areas than in forests. We used a recent estimate of 90 000 individuals as the population size in Sweden, and assumed a stable starting population not affected by mortality from wind turbines. In the absence of data from Sweden, we used demographic data and fatality rates at wind turbines (0.9 noctules/turbine/year) obtained in eastern Germany. Population development up to year 2020 was calculated, based on the current estimate of wind farm development in Sweden; ca. 1000 present and 2500 additional turbines within the area of noctule distribution. The results suggest that the additional mortality at wind turbines may affect the noctule bat in Sweden at the population level. However, the effect will probably be small, particularly in comparison with other anthropogenic sources. We are currently using the model to predict the effect on other bat species and birds. (Author)
Disturbance History,Spatial Variability, and Patterns of Biodiversity
Bendix, J.; Wiley, J. J.; Commons, M.
2012-12-01
The intermediate disturbance hypothesis predicts that species diversity will be maximized in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting combined impact of the magnitude of disturbance and the time since it occurred. We modeled the changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance. Model outputs show that individual landscape patches have highly variable species richness through time, with the details reflecting the timing, intensity and sequence of their disturbance history. When the results are mapped across the landscape, the resulting temporal and spatial complexity illustrates both the contingent nature of diversity and the danger of generalizing about the impacts of disturbance.
A review on the young history of the wind power short-term prediction
DEFF Research Database (Denmark)
Costa, A.; Crespo, A.; Navarro, J.
2008-01-01
This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly...
Wind Plant Performance Prediction (WP3) Project
Energy Technology Data Exchange (ETDEWEB)
Craig, Anna [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-01-26
The methods for analysis of operational wind plant data are highly variable across the wind industry, leading to high uncertainties in the validation and bias-correction of preconstruction energy estimation methods. Lack of credibility in the preconstruction energy estimates leads to significant impacts on project financing and therefore the final levelized cost of energy for the plant. In this work, the variation in the evaluation of a wind plant's operational energy production as a result of variations in the processing methods applied to the operational data is examined. Preliminary results indicate that selection of the filters applied to the data and the filter parameters can have significant impacts in the final computed assessment metrics.
Wind energy availability above gaps in a forest
DEFF Research Database (Denmark)
Sogachev, Andrey; Mann, Jakob; Dellwik, Ebba
2009-01-01
installation strategies. The canopy-planetary boundary-layer model SCADIS is used to investigate the effect of forest gap size (within the diameter range of 3 - 75 tree heights, h) on wind energy related variables. A wind turbine was assumed with following features: the hub height and rotor diameter of 3.5h...... were estimated from modelled data. The results show that the effect of the forest gaps with diameters smaller than 55h on wind energy captured by the assumed wind turbine and located in the centre of round low-roughness gap is practically insignificant. The high level of spatial variation of considered......There is a lack of data on availability of wind energy above a forest disturbed by clear-cuts, where a wind energy developer may find an opportunity to install a wind farm. Computational fluid dynamics (CFD) models can provide spatial patterns of wind and turbulence, and help to develop optimal...
Localization of wind power plants: the aspects of environment and safety
Energy Technology Data Exchange (ETDEWEB)
1982-08-25
The appraisement of the anticipated effects of the wind power on the environment is presented. The following factors are observed: the safety of the plants, noise, infrasound, disturbance of lights and television as well as the effects on nature and birds. Large land based plants with horisontal axis are studied. The risk for a person to be hit by a piece of blade is calculated to 1 x 10 /sup -7/ per million hours. A piece of ice can be thrown up to 250 m in the direction of wind at its highest velocity. The mechanism of nnoise is not well known. The elimination of the disturbance of telecommunication can be attained. Other effects are difficult to quantify and could possibly be manipulated. The distance between human activities and a wind power plant is recommended to be 250 m.
Energy Technology Data Exchange (ETDEWEB)
Wang, Na; Wright, Alan D.; Johnson, Kathryn E.
2016-08-01
Two independent pitch controllers (IPCs) based on the disturbance accommodating control (DAC) algorithm are designed for the three-bladed Controls Advanced Research Turbine to regulate rotor speed and to mitigate blade root flapwise bending loads in above-rated wind speed. One of the DAC-based IPCs is designed based on a transformed symmetrical-asymmetrical (TSA) turbine model, with wind disturbances being modeled as a collective horizontal component and an asymmetrical linear shear component. Another DAC-based IPC is designed based on a multiblade coordinate (MBC) transformed turbine model, with a horizontal component and a vertical shear component being modeled as step waveform disturbance. Both of the DAC-based IPCs are found via a regulation equation solved by Kronecker product. Actuator dynamics are considered in the design processes to compensate for actuator phase delay. The simulation study shows the effectiveness of the proposed DAC-based IPCs compared to a proportional-integral (PI) collective pitch controller (CPC). Improvement on rotor speed regulation and once-per-revolution and twice-per-revolution load reductions has been observed in the proposed IPC designs.
Directory of Open Access Journals (Sweden)
H. Bassi
2017-04-01
Full Text Available Advancements in wind energy technologies have led wind turbines from fixed speed to variable speed operation. This paper introduces an innovative version of a variable-speed wind turbine based on a model predictive control (MPC approach. The proposed approach provides maximum power point tracking (MPPT, whose main objective is to capture the maximum wind energy in spite of the variable nature of the wind’s speed. The proposed MPC approach also reduces the constraints of the two main functional parts of the wind turbine: the full load and partial load segments. The pitch angle for full load and the rotating force for the partial load have been fixed concurrently in order to balance power generation as well as to reduce the operations of the pitch angle. A mathematical analysis of the proposed system using state-space approach is introduced. The simulation results using MATLAB/SIMULINK show that the performance of the wind turbine with the MPC approach is improved compared to the traditional PID controller in both low and high wind speeds.
Power quality improvement of a stand-alone power system subjected to various disturbances
Lone, Shameem Ahmad; Mufti, Mairaj Ud-Din
In wind-diesel stand-alone power systems, the disturbances like random nature of wind power, turbulent wind, sudden changes in load demand and the wind park disconnection effect continuously the system voltage and frequency. The satisfactory operation of such a system is not an easy task and the control design has to take in to account all these subtleties. For maintaining the power quality, generally, a short-term energy storage device is used. In this paper, the performance of a wind-diesel system associated with a superconducting magnetic energy storage (SMES) system is studied. The effect of installing SMES at wind park bus/load bus, on the system performance is investigated. To control the exchange of real and reactive powers between the SMES unit and the wind-diesel system, a control strategy based on fuzzy logic is proposed. The dynamic models of the hybrid power system for most common scenarios are developed and the results presented.
Rodionova, Olga; Sridhar, Banavar; Ng, Hok K.
2016-01-01
Air traffic in the North Atlantic oceanic airspace (NAT) experiences very strong winds caused by jet streams. Flying wind-optimal trajectories increases individual flight efficiency, which is advantageous when operating in the NAT. However, as the NAT is highly congested during peak hours, a large number of potential conflicts between flights are detected for the sets of wind-optimal trajectories. Conflict resolution performed at the strategic level of flight planning can significantly reduce the airspace congestion. However, being completed far in advance, strategic planning can only use predicted environmental conditions that may significantly differ from the real conditions experienced further by aircraft. The forecast uncertainties result in uncertainties in conflict prediction, and thus, conflict resolution becomes less efficient. This work considers wind uncertainties in order to improve the robustness of conflict resolution in the NAT. First, the influence of wind uncertainties on conflict prediction is investigated. Then, conflict resolution methods accounting for wind uncertainties are proposed.
Tian, Lin-Lin; Zhao, Ning; Song, Yi-Lei; Zhu, Chun-Ling
2018-05-01
This work is devoted to perform systematic sensitivity analysis of different turbulence models and various inflow boundary conditions in predicting the wake flow behind a horizontal axis wind turbine represented by an actuator disc (AD). The tested turbulence models are the standard k-𝜀 model and the Reynolds Stress Model (RSM). A single wind turbine immersed in both uniform flows and in modeled atmospheric boundary layer (ABL) flows is studied. Simulation results are validated against the field experimental data in terms of wake velocity and turbulence intensity.
International Nuclear Information System (INIS)
Ghasemian, Masoud; Nejat, Amir
2015-01-01
Highlights: • The noise predictions are performed by Ffowcs Williams and Hawkings method. • There is a direct relation between the radiated noise and the wind speed. • The tonal peaks in the sound spectra match with the blade passing frequency. • The quadrupole noises have negligible effect on the low frequency noises. - Abstract: This paper presents the results of the aerodynamic and aero-acoustic prediction of the flow field around the National Renewable Energy Laboratory Phase VI wind turbine. The Improved Delayed Detached Eddy Simulation turbulence model is applied to obtain the instantaneous turbulent flow field. The noise prediction is carried out using the Ffowcs Williams and Hawkings acoustic analogy. Simulations are performed for three different inflow conditions, U = 7, 10, 15 m/s. The capability of the Improved Delayed Detached Eddy Simulation turbulence model in massive separation is verified with available experimental data for pressure coefficient. The broadband noises of the turbulent boundary layers and the tonal noises due to the blade passing frequency are predicted via flow field noise simulation. The contribution of the thickness, loading and quadrupole noises are investigated, separately. The results indicated that there is a direct relation between the strength of the radiated noise and the wind speed. Furthermore, the effect of the receiver location on the Overall Sound Pressure Level is investigated
Modelling and Measuring Flow and Wind Turbine Wakes in Large Wind Farms Offshore
DEFF Research Database (Denmark)
Barthelmie, Rebecca Jane; Hansen, Kurt Schaldemose; Frandsen, Sten Tronæs
2009-01-01
power losses due to wakes and loads. The research presented is part of the EC-funded UpWind project, which aims to radically improve wind turbine and wind farm models in order to continue to improve the costs of wind energy. Reducing wake losses, or even reduce uncertainties in predicting power losses...
A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines
International Nuclear Information System (INIS)
Song, Zhanfeng; Shi, Tingna; Xia, Changliang; Chen, Wei
2012-01-01
A novel adaptive current controller for DFIG-based wind turbines is introduced in this paper. The attractiveness of the proposed strategy results from its ability to actively estimate and actively compensate for the plant dynamics and external disturbances in real time. Thus, the control strategy can successfully drive the rotor current to track the reference value, ensuring that the performance degradation caused by grid disturbances, cross-coupling terms and parameter uncertainties can be successfully suppressed. Besides, the two-parameter tuning feature makes the control strategy practical and easy to implement in commercial wind turbines. To quantify the controller performances, the transfer function description of the controller is derived. General disturbance rejection, robustness against parameter uncertainties, bandwidth and stability are also addressed. Simulation results, together with the time-domain responses, proved the stability and the strong robustness of the control system against parameter uncertainties and grid disturbances. Significant tracking and disturbance rejection performances are achieved. -- Highlights: ► The controller can compensate for plant dynamics and external disturbances. ► Performance degradation caused by disturbance can be successfully suppressed. ► General disturbance rejection of the proposed strategy is addressed. ► The stability and the strong robustness of the control system are proved.
Huang, Cong; Xu, Ji-Yao; Zhang, Xiao-Xin; Liu, Dan-Dan; Yuan, Wei; Jiang, Guo-Ying
2018-04-01
In this work, we utilize thermospheric wind observations by the Fabry-Perot interferometers (FPI) from the Kelan (KL) station (38.7°N, 111.6°E, Magnetic Latitude: 28.9°N) and the Xinglong (XL) station (40.2°N, 117.4°E, Magnetic Latitude: 30.5°N) in central China during the St. Patrick's Day storm (from Mar. 17 to Mar. 19) of 2015 to analyze thermospheric wind disturbances and compare observations with the Horizontal Wind Model 2007 (HWM07). The results reveal that the wind measurements at KL show very similar trends to those at XL. Large enhancements are seen in both the westward and equatorward winds after the severe geomagnetic storm occurred. The westward wind speed increased to a peak value of 75 m/s and the equatorward wind enhanced to a peak value of over 100 m/s. There also exist obvious poleward disturbances in the meridional winds during Mar. 17 to Mar. 19. According to the comparison with HWM07, there exist evident wind speed and temporal differences between FPI-winds and the model outputs in this severe geomagnetic storm. The discrepancies between the observations and HWM07 imply that the empirical model should be used carefully in wind disturbance forecast during large geomagnetic storms and more investigations between measurements and numerical models are necessary in future studies.
Aerodynamical errors on tower mounted wind speed measurements due to the presence of the tower
Energy Technology Data Exchange (ETDEWEB)
Bergstroem, H. [Uppsala Univ. (Sweden). Dept. of Meteorology; Dahlberg, J.Aa. [Aeronautical Research Inst. of Sweden, Bromma (Sweden)
1996-12-01
Field measurements of wind speed from two lattice towers showed large differences for wind directions where the anemometers of both towers should be unaffected by any upstream obstacle. The wind speed was measured by cup anemometers mounted on booms along the side of the tower. A simple wind tunnel test indicates that the boom, for the studied conditions, could cause minor flow disturbances. A theoretical study, by means of simple 2D flow modelling of the flow around the mast, demonstrates that the tower itself could cause large wind flow disturbances. A theoretical study, based on simple treatment of the physics of motion of a cup anemometer, demonstrates that a cup anemometer is sensitive to velocity gradients across the cups and responds clearly to velocity gradients in the vicinity of the tower. Comparison of the results from the theoretical study and field tests show promising agreement. 2 refs, 8 figs
Effects of wind turbines on upland nesting birds in Conservation Reserve Program grasslands
Leddy, K.L.; Higgins, K.F.; Naugle, D.E.
1999-01-01
Grassland passerines were surveyed during summer 1995 on the Buffalo Ridge Wind Resource Area in southwestern Minnesota to determine the relative influence of wind turbines on overall densities of upland nesting birds in Conservation Reserve Program (CRP) grasslands. Birds were surveyed along 40 m fixed width transects that were placed along wind turbine strings within three CRP fields and in three CRP fields without turbines. Conservation Reserve Program grasslands without turbines and areas located 180 m from turbines supported higher densities (261.0-312.5 males/100 ha) of grassland birds than areas within 80 m of turbines (58.2-128.0 males/100 ha). Human disturbance, turbine noise, and physical movements of turbines during operation may have disturbed nesting birds. We recommend that wind turbines be placed within cropland habitats that support lower densities of grassland passerines than those found in CRP grasslands.
Impact of wind turbines on birds
International Nuclear Information System (INIS)
Clausager, I.; Nohr, H.
1996-01-01
The paper is a review of the present knowledge on impacts of wind turbines on birds, requested by the Danish Ministry of the Environment and Energy. The main conclusions of the review are, that in nearly all the studies so far the numbers of birds recorded colliding with wind turbines have been limited. Some studies indicate that stationary (breeding) birds inside the wind turbine area in the short run habituate to wind turbines, especially the noise and visual impacts, and that the risk for collision becomes low. However, some of the few more long term studies indicate that a negative impact may occur in later generations of breeding birds. In some studies a disturbance effect on bird species, which temporarily stay inside a wind turbine area in order to forage or rest, is observed. The degree of impact is species-specific. An effect is typically recorded inside a zone of up to 250-800 m, with geese and waders as the most sensitive groups of birds. (author)
National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...
Health effects related to wind turbine noise exposure: a systematic review.
Schmidt, Jesper Hvass; Klokker, Mads
2014-01-01
Wind turbine noise exposure and suspected health-related effects thereof have attracted substantial attention. Various symptoms such as sleep-related problems, headache, tinnitus and vertigo have been described by subjects suspected of having been exposed to wind turbine noise. This review was conducted systematically with the purpose of identifying any reported associations between wind turbine noise exposure and suspected health-related effects. A search of the scientific literature concerning the health-related effects of wind turbine noise was conducted on PubMed, Web of Science, Google Scholar and various other Internet sources. All studies investigating suspected health-related outcomes associated with wind turbine noise exposure were included. Wind turbines emit noise, including low-frequency noise, which decreases incrementally with increases in distance from the wind turbines. Likewise, evidence of a dose-response relationship between wind turbine noise linked to noise annoyance, sleep disturbance and possibly even psychological distress was present in the literature. Currently, there is no further existing statistically-significant evidence indicating any association between wind turbine noise exposure and tinnitus, hearing loss, vertigo or headache. Selection bias and information bias of differing magnitudes were found to be present in all current studies investigating wind turbine noise exposure and adverse health effects. Only articles published in English, German or Scandinavian languages were reviewed. Exposure to wind turbines does seem to increase the risk of annoyance and self-reported sleep disturbance in a dose-response relationship. There appears, though, to be a tolerable level of around LAeq of 35 dB. Of the many other claimed health effects of wind turbine noise exposure reported in the literature, however, no conclusive evidence could be found. Future studies should focus on investigations aimed at objectively demonstrating whether or not
Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation
Directory of Open Access Journals (Sweden)
J. M. Torres
2018-01-01
Full Text Available Making every component of an electrical system work in unison is being made more challenging by the increasing number of renewable energies used, the electrical output of which is difficult to determine beforehand. In Spain, the daily electricity market opens with a 12-hour lead time, where the supply and demand expected for the following 24 hours are presented. When estimating the generation, energy sources like nuclear are highly stable, while peaking power plants can be run as necessary. Renewable energies, however, which should eventually replace peakers insofar as possible, are reliant on meteorological conditions. In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. We develop and compare various estimators based on feedforward, convolutional, and recurrent neural networks. These estimators were trained and validated with data from a wind farm located on the island of Tenerife. We show that the best candidates for each type are more precise than the reference estimator and the polynomial regression currently used at the wind farm. We also conduct a sensitivity analysis to determine which estimator type is most robust to perturbations. An analysis of our findings shows that the most accurate and robust estimators are those based on feedforward neural networks with a SELU activation function and convolutional neural networks.
DEFF Research Database (Denmark)
Alessandrini, S.; Sperati, S.; Pinson, Pierre
2013-01-01
together with a single forecast power value for each future time horizon. A comparison between two different ensemble forecasting models, ECMWF EPS (Ensemble Prediction System in use at the European Centre for Medium-Range Weather Forecasts) and COSMO-LEPS (Limited-area Ensemble Prediction System developed...... ahead forecast horizon. A statistical calibration of the ensemble wind speed members based on the use of past wind speed measurements is explained. The two models are compared using common verification indices and diagrams. The higher horizontal resolution model (COSMO-LEPS) shows slightly better...
DEFF Research Database (Denmark)
Trombe, Pierre-Julien; Pinson, Pierre; Madsen, Henrik
2011-01-01
The substantial impact of wind power fluctuations at large offshore wind farms calls for the development of dedicated monitoring and prediction approaches. Based on recent findings, a Local Area Weather Radar (LAWR) was installed at Horns Rev with the aim of improving predictability, controlability...... and potentially maintenance planning. Additional images are available from a Doppler radar covering the same area. The parallel analysis of rain events detection and of regime sequences in wind (and power) fluctuations demonstrates the interest of employing weather radars for a better operation and management...... of offshore wind farms....
Impact of Wind Power Plants with Full Converter Wind Turbines on Power System Small-Signal Stability
DEFF Research Database (Denmark)
Knüppel, Thyge; Nygaard Nielsen, Jørgen; Dixon, Andrew
Wind power is being developed in power systems all around the world, and already today wind power covers more than 20 % of the electricity consumption in some countries. As the size of each wind power plant (WPP) increases and as the levels of penetration reaches certain magnitudes, the inclusion...... of the dynamic properties of the WPPs in the power system stability studies become important. The work presented in this report deal with the impact of WPPs based on full converter wind turbines (WTs) on the power system small-signal rotor angle stability. During small disturbances in the power system, the rotor...... speed of the synchronous machines will eventually return to its steady state if the power system is small-signal stable. The dynamic properties of a WPP are fundamentally dierent from those of a synchronous machine, and the interaction of WPPs with the synchronous machines in power system oscillations...
Wang, Yong; Yu, Zong-Fan; Cheng, Yun-Sheng; Jia, Ben-Li; Yu, Gang; Yin, Xiao-Qiang; Wang, Yang
2017-07-01
This study is all about predicting the value of serum vaspin level in the amelioration of fatty liver and metabolic disturbance in patients with severe obesity after laparoscopic vertical banded gastroplasty (LVBG). A total of 164 patients (from January 2012 to May 2015) with severe obesity were chosen and performed LVBG. Enzyme-linked immunosorbent assay was performed to detect the serum vaspin level. The patients were given a biochemical automatic analyzer to measure the biochemical indicators. Homeostasis model assessment (HOMA) helps in the calculation of fasting insulin level (FINS) and insulin resistance (IR). The changes in fatty liver were examined by computed tomography (CT). Receiver operating characteristic curve is used to increase the predictive value of serum vaspin level in the amelioration of liver function and disturbances in the metabolism. Weight, BMI, waist circumference, serum vaspin level, and triglyceride (TG) decreased, but CT value of liver increased at 4th, 7th, and 12th month after surgery. After the 7th and 12th month period of surgery, the alanine aminotransferase, aspartate aminotransferase, FINS, and HOMA-IR reduced in the patients (P fatty liver and metabolic disturbance. This study proves that the serum vaspin level serves as a predictive indicator in the amelioration of fatty liver and metabolic disturbance in patients with severe obesity after LVBG.
Directory of Open Access Journals (Sweden)
Maria Grazia De Giorgi
2014-08-01
Full Text Available A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP. A comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain. The performances of Least-Squares Support Vector Machine (LS-SVM with Wavelet Decomposition (WD were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN-based methods. It is acknowledged that hybrid methods based on LS-SVM with WD mostly outperform other methods. A decomposition of the commonly known root mean square error was beneficial for a better understanding of the origin of the differences between prediction and measurement and to compare the accuracy of the different models. A sensitivity analysis was also carried out in order to underline the impact that each input had in the network training process for ANN. In the case of ANN with the WD technique, the sensitivity analysis was repeated on each component obtained by the decomposition.
Venzmer, M. S.; Bothmer, V.
2018-03-01
Context. The Parker Solar Probe (PSP; formerly Solar Probe Plus) mission will be humanitys first in situ exploration of the solar corona with closest perihelia at 9.86 solar radii (R⊙) distance to the Sun. It will help answer hitherto unresolved questions on the heating of the solar corona and the source and acceleration of the solar wind and solar energetic particles. The scope of this study is to model the solar-wind environment for PSPs unprecedented distances in its prime mission phase during the years 2018 to 2025. The study is performed within the Coronagraphic German And US SolarProbePlus Survey (CGAUSS) which is the German contribution to the PSP mission as part of the Wide-field Imager for Solar PRobe. Aim. We present an empirical solar-wind model for the inner heliosphere which is derived from OMNI and Helios data. The German-US space probes Helios 1 and Helios 2 flew in the 1970s and observed solar wind in the ecliptic within heliocentric distances of 0.29 au to 0.98 au. The OMNI database consists of multi-spacecraft intercalibrated in situ data obtained near 1 au over more than five solar cycles. The international sunspot number (SSN) and its predictions are used to derive dependencies of the major solar-wind parameters on solar activity and to forecast their properties for the PSP mission. Methods: The frequency distributions for the solar-wind key parameters, magnetic field strength, proton velocity, density, and temperature, are represented by lognormal functions. In addition, we consider the velocity distributions bi-componental shape, consisting of a slower and a faster part. Functional relations to solar activity are compiled with use of the OMNI data by correlating and fitting the frequency distributions with the SSN. Further, based on the combined data set from both Helios probes, the parameters frequency distributions are fitted with respect to solar distance to obtain power law dependencies. Thus an empirical solar-wind model for the inner
Geomagnetic response to solar and interplanetary disturbances
Directory of Open Access Journals (Sweden)
Maris Georgeta
2013-07-01
Full Text Available The space weather discipline involves different physical scenarios, which are characterised by very different physical conditions, ranging from the Sun to the terrestrial magnetosphere and ionosphere. Thanks to the great modelling effort made during the last years, a few Sun-to-ionosphere/thermosphere physics-based numerical codes have been developed. However, the success of the prediction is still far from achieving the desirable results and much more progress is needed. Some aspects involved in this progress concern both the technical progress (developing and validating tools to forecast, selecting the optimal parameters as inputs for the tools, improving accuracy in prediction with short lead time, etc. and the scientific development, i.e., deeper understanding of the energy transfer process from the solar wind to the coupled magnetosphere-ionosphere-thermosphere system. The purpose of this paper is to collect the most relevant results related to these topics obtained during the COST Action ES0803. In an end-to-end forecasting scheme that uses an artificial neural network, we show that the forecasting results improve when gathering certain parameters, such as X-ray solar flares, Type II and/or Type IV radio emission and solar energetic particles enhancements as inputs for the algorithm. Regarding the solar wind-magnetosphere-ionosphere interaction topic, the geomagnetic responses at high and low latitudes are considered separately. At low latitudes, we present new insights into temporal evolution of the ring current, as seen by Burton’s equation, in both main and recovery phases of the storm. At high latitudes, the PCC index appears as an achievement in modelling the coupling between the upper atmosphere and the solar wind, with a great potential for forecasting purposes. We also address the important role of small-scale field-aligned currents in Joule heating of the ionosphere even under non-disturbed conditions. Our scientific results in
Seasonal Dependence of Geomagnetic Active-Time Northern High-Latitude Upper Thermospheric Winds
Dhadly, Manbharat S.; Emmert, John T.; Drob, Douglas P.; Conde, Mark G.; Doornbos, Eelco; Shepherd, Gordon G.; Makela, Jonathan J.; Wu, Qian; Nieciejewski, Richard J.; Ridley, Aaron J.
2018-01-01
This study is focused on improving the poorly understood seasonal dependence of northern high-latitude F region thermospheric winds under active geomagnetic conditions. The gaps in our understanding of the dynamic high-latitude thermosphere are largely due to the sparseness of thermospheric wind measurements. With current observational facilities, it is infeasible to construct a synoptic picture of thermospheric winds, but enough data with wide spatial and temporal coverage have accumulated to construct a meaningful statistical analysis. We use long-term data from eight ground-based and two space-based instruments to derive climatological wind patterns as a function of magnetic local time, magnetic latitude, and season. These diverse data sets possess different geometries and different spatial and solar activity coverage. The major challenge is to combine these disparate data sets into a coherent picture while overcoming the sampling limitations and biases among them. In our previous study (focused on quiet time winds), we found bias in the Gravity Field and Steady State Ocean Circulation Explorer (GOCE) cross-track winds. Here we empirically quantify the GOCE bias and use it as a correction profile for removing apparent bias before empirical wind formulation. The assimilated wind patterns exhibit all major characteristics of high-latitude neutral circulation. The latitudinal extent of duskside circulation expands almost 10∘ from winter to summer. The dawnside circulation subsides from winter to summer. Disturbance winds derived from geomagnetic active and quiet winds show strong seasonal and latitudinal variability. Comparisons between wind patterns derived here and Disturbance Wind Model (DWM07) (which have no seasonal dependence) suggest that DWM07 is skewed toward summertime conditions.
International Nuclear Information System (INIS)
Van den Bergh, L.M.J.; Spaans, A.L.
1993-01-01
The title farm comprises 16 three-bladed 500 kW wind turbines. Hindrance of wind turbines are collisions with the wind turbines and in the wake behind the blades and loss or disintegration of the natural habitat because of the presence of the wind turbines (aspect of disturbance). The title study is focused on counting the number of collision bird victims per year, and analyzing the disturbance effects on hibernating and foraging birds. It appeared that almost 150 to more than 1500 birds will collide with one of the 16 wind turbines. A few hundred tufted ducks, some tens of pochard and some tens of wild ducks per kilometre of the wind farm will leave their natural habitat. Based on the results it is concluded that the dike area between kilometre marker 32.5 and kilometre marker 35.5 is the most suitable area for a wind turbine array along the Zuidermeerdijk in between Schokkerhaven and Ketelbrug, both Netherlands. 3 figs., 5 tabs., 2 appendices, 33 refs
Energy Technology Data Exchange (ETDEWEB)
Nakamura, S.; Nagamachi, K.; Kawai, Y. [Kawasaki Steel Corp., Tokyo (Japan); Kimura, K.; Fujino, Y. [The University of Tokyo, Tokyo (Japan). Faculty of Engineering; Tanaka, H.
1996-03-01
This paper outlines the vertical gust response analysis method in a yawed wind, gives an analytic example, and compares the experimental result with the analytic result to investigate the application of an analysis method and the validity of assumption and approximation. The vertical gust response to two cable-stayed bridges under construction in a yawed wind was predicted by applying assumption and approximation to the gust response prediction method in a yawed wind with the cantilever model having a plate cross-section manipulated. In this case, the wind velocity component perpendicular to the leading edge was defined as an effective wind velocity, and a bridge axis and the component perpendicular to a bridge axis were separately calculated in response. Moreover, some aerodynamic coefficients of a bridge girder cross-section were approximately obtained from the characteristics of the flat blades with same aspect ratio. The obtained analytic result was compared with the wind tunnel test result based on all bridge models. The result showed that the former almost coincides with the latter, the assumption and approximation of this time are verified in validity, and this analysis method can be used for cable-stayed bridges under construction. 10 refs., 7 figs., 2 tabs.
Wind data for wind driven plant. [site selection for optimal performance
Stodhart, A. H.
1973-01-01
Simple, averaged wind velocity data provide information on energy availability, facilitate generator site selection and enable appropriate operating ranges to be established for windpowered plants. They also provide a basis for the prediction of extreme wind speeds.
High resolution modelling of wind fields for optimization of empirical storm flood predictions
Brecht, B.; Frank, H.
2014-05-01
High resolution wind fields are necessary to predict the occurrence of storm flood events and their magnitude. Deutscher Wetterdienst (DWD) created a catalogue of detailed wind fields of 39 historical storms at the German North Sea coast from the years 1962 to 2011. The catalogue is used by the Niedersächsisches Landesamt für Wasser-, Küsten- und Naturschutz (NLWKN) coastal research center to improve their flood alert service. The computation of wind fields and other meteorological parameters is based on the model chain of the DWD going from the global model GME via the limited-area model COSMO with 7 km mesh size down to a COSMO model with 2.2 km. To obtain an improved analysis COSMO runs are nudged against observations for the historical storms. The global model GME is initialised from the ERA reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF). As expected, we got better congruency with observations of the model for the nudging runs than the normal forecast runs for most storms. We also found during the verification process that different land use data sets could influence the results considerably.
Energy Technology Data Exchange (ETDEWEB)
Wang, Na; Wright, Alan D.; Johnson, Kathryn E.
2016-07-29
Two independent pitch controllers (IPCs) based on the disturbance accommodating control (DAC) algorithm are designed for the three-bladed Controls Advanced Research Turbine to regulate rotor speed and to mitigate blade root flapwise bending loads in above-rated wind speed. One of the DAC-based IPCs is designed based on a transformed symmetrical-asymmetrical (TSA) turbine model, with wind disturbances being modeled as a collective horizontal component and an asymmetrical linear shear component. Another DAC-based IPC is designed based on a multiblade coordinate (MBC) transformed turbine model, with a horizontal component and a vertical shear component being modeled as step waveform disturbance. Both of the DAC-based IPCs are found via a regulation equation solved by Kronecker product. Actuator dynamics are considered in the design processes to compensate for actuator phase delay. The simulation study shows the effectiveness of the proposed DAC-based IPCs compared to a proportional-integral (PI) collective pitch controller (CPC). Improvement on rotor speed regulation and once-per-revolution and twice-per-revolution load reductions has been observed in the proposed IPC designs.
Van Onselen, Christina; Paul, Steven M; Lee, Kathryn; Dunn, Laura; Aouizerat, Bradley E; West, Claudia; Dodd, Marylin; Cooper, Bruce; Miaskowski, Christine
2013-02-01
Sleep disturbance is a problem for oncology patients. To evaluate how sleep disturbance and daytime sleepiness (DS) changed from before to six months following surgery and whether certain characteristics predicted initial levels and/or the trajectories of these parameters. Patients (n=396) were enrolled prior to surgery and completed monthly assessments for six months following surgery. The General Sleep Disturbance Scale was used to assess sleep disturbance and DS. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of sleep disturbance and DS. All seven General Sleep Disturbance Scale scores were above the cutoff for clinically meaningful levels of sleep disturbance. Lower performance status; higher comorbidity, attentional fatigue, and physical fatigue; and more severe hot flashes predicted higher preoperative levels of sleep disturbance. Higher levels of education predicted higher sleep disturbance scores over time. Higher levels of depressive symptoms predicted higher preoperative levels of sleep disturbance, which declined over time. Lower performance status; higher body mass index; higher fear of future diagnostic tests; not having had sentinel lymph node biopsy; having had an axillary lymph node dissection; and higher depression, physical fatigue, and attentional fatigue predicted higher DS prior to surgery. Higher levels of education, not working for pay, and not having undergone neo-adjuvant chemotherapy predicted higher DS scores over time. Sleep disturbance is a persistent problem for patients with breast cancer. The effects of interventions that can address modifiable risk factors need to be evaluated. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Winkelman, J E
1992-01-01
The title study concerns the period 1984-1991. The wind park consists of 18 three-bladed 300 kW horizontal axis wind turbines of 35 meters height, and a rotor diameter of 30 meters, seven meteorological towers, and three cluster and control buildings. Aspects studied included disturbance of breeding, resting or feeding, and migrating birds, behavior of birds approaching the wind turbines during the day and night, and bird victims due to collision with the wind turbines and the meteorological towers. In this report attention is paid to the disturbance of the bird's biotope. The results show that four species of grassland birds, breeding in the park, were hardly disturbed by the wind turbines. For feeding and resting birds, however, disturbance effects were noted, even at a distance of 500 meters from the outside wind turbine array. The present number of bird species reduced 60-95%, dependent on the species, after the wind park was put into operation. Also the behavior of migrating birds was influenced by the wind park, showed in clustering of groups or avoiding the wind park, sometimes up to 67% of the birds did so. It is therefore recommended not to implement new wind parks in important bird migration and bird feeding or bird resting areas. Bird popular areas, however, are mostly windy areas. 15 figs., 25 tabs., 56 app., 128 refs.
Wind power forecasting: IEA Wind Task 36 & future research issues
DEFF Research Database (Denmark)
Giebel, Gregor; Cline, J.; Frank, Helmut Paul
2016-01-01
the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind Energy tries to organise international collaboration, among national meteorological centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD...
International Nuclear Information System (INIS)
Villalpando, Fernando; Reggio, Marcelo; Ilinca, Adrian
2016-01-01
An approach to numerically simulate ice accretion on 2D sections of a wind turbine blade is presented. The method uses standard commercial ANSYS-Fluent and Matlab tools. The Euler-Euler formulation is used to calculate the water impingement on the airfoil, and a UDF (Used Defined Function) has been devised to turn the airfoil's solid wall into a permeable boundary. Mayer's thermodynamic model is implemented in Matlab for computing ice thickness and for updating the airfoil contour. A journal file is executed to systematize the procedure: meshing, droplet trajectory calculation, thermodynamic model application for computing ice accretion, and the updating of airfoil contours. The proposed ice prediction strategy has been validated using iced airfoil contours obtained experimentally in the AMIL refrigerated wind tunnel (Anti-icing Materials International Laboratory). Finally, a numerical prediction method has been generated for anti-icing assessment, and its results compared with data obtained in this laboratory. - Highlights: • A methodology for ice accretion prediction using commercial software is proposed. • Euler model gives better prediction of airfoil water collection with detached flow. • A source term is used to change from a solid wall to a permeable wall in Fluent. • Energy needed for ice-accretion mitigation system is predicted.
Falcone, James A.; Carlisle, Daren M.; Weber, Lisa C.
2010-01-01
Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.
Bakker, R.H.; Pedersen, E.; Berg, G.P. van den; Stewart, R.E.; Lok, W.; Bouma, J.
2012-01-01
Purpose of the research: The present government in the Netherlands intends to realize a substantial growth of wind energy before 2020, both onshore and offshore. Wind turbines, when positioned in the neighborhood of residents may cause visual annoyance and noise annoyance. Studies on other
Accurate wind farm development and operation. Advanced wake modelling
Energy Technology Data Exchange (ETDEWEB)
Brand, A.; Bot, E.; Ozdemir, H. [ECN Unit Wind Energy, P.O. Box 1, NL 1755 ZG Petten (Netherlands); Steinfeld, G.; Drueke, S.; Schmidt, M. [ForWind, Center for Wind Energy Research, Carl von Ossietzky Universitaet Oldenburg, D-26129 Oldenburg (Germany); Mittelmeier, N. REpower Systems SE, D-22297 Hamburg (Germany))
2013-11-15
The ability is demonstrated to calculate wind farm wakes on the basis of ambient conditions that were calculated with an atmospheric model. Specifically, comparisons are described between predicted and observed ambient conditions, and between power predictions from three wind farm wake models and power measurements, for a single and a double wake situation. The comparisons are based on performance indicators and test criteria, with the objective to determine the percentage of predictions that fall within a given range about the observed value. The Alpha Ventus site is considered, which consists of a wind farm with the same name and the met mast FINO1. Data from the 6 REpower wind turbines and the FINO1 met mast were employed. The atmospheric model WRF predicted the ambient conditions at the location and the measurement heights of the FINO1 mast. May the predictability of the wind speed and the wind direction be reasonable if sufficiently sized tolerances are employed, it is fairly impossible to predict the ambient turbulence intensity and vertical shear. Three wind farm wake models predicted the individual turbine powers: FLaP-Jensen and FLaP-Ainslie from ForWind Oldenburg, and FarmFlow from ECN. The reliabilities of the FLaP-Ainslie and the FarmFlow wind farm wake models are of equal order, and higher than FLaP-Jensen. Any difference between the predictions from these models is most clear in the double wake situation. Here FarmFlow slightly outperforms FLaP-Ainslie.
Estimation of the uncertainty in wind power forecasting
International Nuclear Information System (INIS)
Pinson, P.
2006-03-01
WIND POWER experiences a tremendous development of its installed capacities in Europe. Though, the intermittence of wind generation causes difficulties in the management of power systems. Also, in the context of the deregulation of electricity markets, wind energy is penalized by its intermittent nature. It is recognized today that the forecasting of wind power for horizons up to 2/3-day ahead eases the integration of wind generation. Wind power forecasts are traditionally provided in the form of point predictions, which correspond to the most-likely power production for a given horizon. That sole information is not sufficient for developing optimal management or trading strategies. Therefore, we investigate on possible ways for estimating the uncertainty of wind power forecasts. The characteristics of the prediction uncertainty are described by a thorough study of the performance of some of the state-of-the-art approaches, and by underlining the influence of some variables e.g. level of predicted power on distributions of prediction errors. Then, a generic method for the estimation of prediction intervals is introduced. This statistical method is non-parametric and utilizes fuzzy logic concepts for integrating expertise on the prediction uncertainty characteristics. By estimating several prediction intervals at once, one obtains predictive distributions of wind power output. The proposed method is evaluated in terms of its reliability, sharpness and resolution. In parallel, we explore the potential use of ensemble predictions for skill forecasting. Wind power ensemble forecasts are obtained either by converting meteorological ensembles (from ECMWF and NCEP) to power or by applying a poor man's temporal approach. A proposal for the definition of prediction risk indices is given, reflecting the disagreement between ensemble members over a set of successive look-ahead times. Such prediction risk indices may comprise a more comprehensive signal on the expected level
Directory of Open Access Journals (Sweden)
Evans Samuel P.
2017-01-01
Full Text Available This paper investigates the applicability of the assumed wind fields in International Electrotechnical Commission (IEC standard 61400 Part 2, the design standard for small wind turbines, for a turbine operating in the built environment, and the effects these wind fields have on the predicted performance of a 5 kW Aerogenesis turbine using detailed aeroelastic models developed in Fatigue Aerodynamics Structures and Turbulence (FAST. Detailed wind measurements were acquired at two built environment sites: from the rooftop of a Bunnings Ltd. warehouse at Port Kennedy (PK (Perth, Australia and from the small wind turbine site at the University of Newcastle at Callaghan (Newcastle, Australia. For both sites, IEC 61400-2 underestimates the turbulence intensity for the majority of the measured wind speeds. A detailed aeroelastic model was built in FAST using the assumed wind field from IEC 61400-2 and the measured wind fields from PK and Callaghan as an input to predict key turbine performance parameters. The results of this analysis show a modest increase in the predicted mean power for the higher turbulence regimes of PK and Callaghan as well as higher variation in output power. Predicted mean rotor thrust and blade flapwise loading showed a minor increase due to higher turbulence, with mean predicted torque almost identical but with increased variations due to higher turbulence. Damage equivalent loading for the blade flapwise moment was predicted to be 58% and 11% higher for a turbine operating at Callaghan and PK respectively, when compared with IEC 61400-2 wind field. Time series plots for blade flapwise moments and power spectral density plots in the frequency domain show consistently higher blade flapwise bending moments for the Callaghan site with both the sites showing a once-per-revolution response.
Wind response in the lower thermosphere to the geomagnetic storm on March, 1989
International Nuclear Information System (INIS)
Kazimirovskij, Eh.S.; Vergasova, G.V.
1991-01-01
The horizontal wind response in the ionospheric D region above Irkutsk to the geomagnetic storm on March 13, 1989 is studied. The geomagnetic storm response is expressed through a stability loss of the wind system, a great speed increase of the meridional and zonal wind, in particular, and their dispersions, respectively, as well as changes in the semidaily tidal phase. The proof of the fact that the Earth magnetic field disturbances destabilize the system of horizontal winds in the lower ionosphere is given
An Optimization-Based System Model of Disturbance-Generated Forest Biomass Utilization
Curry, Guy L.; Coulson, Robert N.; Gan, Jianbang; Tchakerian, Maria D.; Smith, C. Tattersall
2008-01-01
Disturbance-generated biomass results from endogenous and exogenous natural and cultural disturbances that affect the health and productivity of forest ecosystems. These disturbances can create large quantities of plant biomass on predictable cycles. A systems analysis model has been developed to quantify aspects of system capacities (harvest,…
Aggregated wind power generation probabilistic forecasting based on particle filter
International Nuclear Information System (INIS)
Li, Pai; Guan, Xiaohong; Wu, Jiang
2015-01-01
Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method
Dependence of optimal wind turbine spacing on wind farm length
Stevens, Richard Johannes Antonius Maria
2016-01-01
Recent large eddy simulations have led to improved parameterizations of the effective roughness height of wind farms. This effective roughness height can be used to predict the wind velocity at hub-height as function of the geometric mean of the spanwise and streamwise turbine spacings and the
Rezaeiha, A.; Kalkman, I.; Blocken, B.J.E.
2017-01-01
Accurate prediction of the performance of a vertical-axis wind turbine (VAWT) using CFD simulation requires the employment of a sufficiently fine azimuthal increment (dθ) combined with a mesh size at which essential flow characteristics can be accurately resolved. Furthermore, the domain size needs
International Nuclear Information System (INIS)
Abderrazzaq, M.H.; Aloquili, O.
2008-01-01
The growth of wind energy is attributed to the development of turbine size and the increase in number of units in each wind farm. The current modern design of large wind turbines (WT) is directed towards producing efficient, sensitive and reliable units. To achieve this goal, modern turbines are equipped with several devices which are operated with highly advanced electronic circuits. Sensing instruments, measuring devices and control processes of major systems and subsystems are based on various types of electronic apparatus and boards. These boards are very sensitive to the voltage variations caused by abnormal conditions in both the turbine itself and the electric grid to which the wind farm is connected. This paper evaluates wind farm records and proposes a number of methods to overcome such obstacles associated with the design of large wind turbines. Several cases of grid abnormality such as sudden feeder interruption due to the short circuit, network disconnection, voltage variation and circuit breaker opening affecting wind turbines operation and availability are classified and presented. The weight of such impact is determined for each type of disturbances associated with electronic problems in the wind turbine. Wind turbine performance at Hofa wind farm scheme in Jordan is taken as a case study
Dodson, R. O., Jr.
1982-01-01
One of the objectives of the KC-135 Winglet Flight Research and Demonstration Program was to obtain experimental flight test data to verify the theoretical and wind tunnel winglet aerodynamic performance prediction methods. Good agreement between analytic, wind tunnel and flight test performance was obtained when the known differences between the tests and analyses were accounted for. The flight test measured fuel mileage improvements for a 0.78 Mach number was 3.1 percent at 8 x 10(5) pounds W/delta and 5.5 percent at 1.05 x 10(6) pounds W/delta. Correcting the flight measured data for surface pressure differences between wind tunnel and flight resulted in a fuel mileage improvement of 4.4 percent at 8 x 10(5) pounds W/delta and 7.2 percent at 1.05 x 10(6) pounds W/delta. The performance improvement obtained was within the wind tunnel test data obtained from two different wind tunnel models. The buffet boundary data obtained for the baseline configuration was in good agreement with previous established data. Buffet data for the 15 deg cant/-4 deg incidence configuration showed a slight improvement, while the 15 deg cant/-2 deg incidence and 0 deg cant/-4 deg incidence data showed a slight deterioration.
Intelligent control for large-scale variable speed variable pitch wind turbines
Institute of Scientific and Technical Information of China (English)
Xinfang ZHANG; Daping XU; Yibing LIU
2004-01-01
Large-scale wind turbine generator systems have strong nonlinear multivariable characteristics with many uncertain factors and disturbances.Automatic control is crucial for the efficiency and reliability of wind turbines.On the basis of simplified and proper model of variable speed variable pitch wind turbines,the effective wind speed is estimated using extended Kalman filter.Intelligent control schemes proposed in the paper include two loops which operate in synchronism with each other.At below-rated wind speed,the inner loop adopts adaptive fuzzy control based on variable universe for generator torque regulation to realize maximum wind energy capture.At above-rated wind speed, a controller based on least square support vector machine is proposed to adjust pitch angle and keep rated output power.The simulation shows the effectiveness of the intelligent control.
On wake modeling, wind-farm gradients and AEP predictions at the Anholt wind farm
DEFF Research Database (Denmark)
Pena Diaz, Alfredo; Hansen, Kurt Schaldemose; Ott, Søren
2017-01-01
of the mesoscale simulations and supervisory control and data acquisition (SCADA), we show that for westerly flow in particular, there is a clear horizontal wind-speed gradient over the wind farm. We also use the mesoscale simulations to derive the undisturbed inflow conditions that are coupled with three commonly....... When looking at westerly flow wake cases, where the impact of the horizontal wind-speed gradient on the power of the undisturbed turbines is largest, the wake models agree with the SCADA fairly well; when looking at a southerly flow case, where the wake losses are highest, the wake models tend...... to underestimate the wake loss. With the mesoscale-wake model setup, we are also able to estimate the capacity factor of the wind farm rather well when compared to that derived from the SCADA. Finally, we estimate the uncertainty of the wake models by bootstrapping the SCADA. The models tend to underestimate...
LIDAR Correlation to Extreme Flapwise Moment : Gust Impact Prediction Time and Feedforward Control
DEFF Research Database (Denmark)
Meseguer Urban, Albert; Hansen, Morten Hartvig
A Conventional wind turbine controller uses feedback parameters reacting to wind disturbances after they have already impacted the rotor. LIDARs are able to measure the wind speed before it reaches the wind turbine rotor. These anticipated values can be used in control systems designed to reduce...
Bell, Terrence H; Yergeau, Etienne; Maynard, Christine; Juck, David; Whyte, Lyle G; Greer, Charles W
2013-06-01
Increased exploration and exploitation of resources in the Arctic is leading to a higher risk of petroleum contamination. A number of Arctic microorganisms can use petroleum for growth-supporting carbon and energy, but traditional approaches for stimulating these microorganisms (for example, nutrient addition) have varied in effectiveness between sites. Consistent environmental controls on microbial community response to disturbance from petroleum contaminants and nutrient amendments across Arctic soils have not been identified, nor is it known whether specific taxa are universally associated with efficient bioremediation. In this study, we contaminated 18 Arctic soils with diesel and treated subsamples of each with monoammonium phosphate (MAP), which has successfully stimulated degradation in some contaminated Arctic soils. Bacterial community composition of uncontaminated, diesel-contaminated and diesel+MAP soils was assessed through multiplexed 16S (ribosomal RNA) rRNA gene sequencing on an Ion Torrent Personal Genome Machine, while hydrocarbon degradation was measured by gas chromatography analysis. Diversity of 16S rRNA gene sequences was reduced by diesel, and more so by the combination of diesel and MAP. Actinobacteria dominated uncontaminated soils with diesel degradation in MAP-treated soils, suggesting this may be an important group to stimulate. The predictability with which bacterial communities respond to these disturbances suggests that costly and time-consuming contaminated site assessments may not be necessary in the future.
Evaluation of Nonparametric Probabilistic Forecasts of Wind Power
DEFF Research Database (Denmark)
Pinson, Pierre; Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg, orlov 31.07.2008
Predictions of wind power production for horizons up to 48-72 hour ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the most...... likely outcome for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from nonparametric methods, and then take the form of a single or a set...
Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms
DEFF Research Database (Denmark)
Barthelmie, Rebecca Jane; Pryor, Sara; Frandsen, Sten Tronæs
2010-01-01
There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms...
Observation and simulation of the ionosphere disturbance waves triggered by rocket exhausts
Lin, Charles C. H.; Chen, Chia-Hung; Matsumura, Mitsuru; Lin, Jia-Ting; Kakinami, Yoshihiro
2017-08-01
Observations and theoretical modeling of the ionospheric disturbance waves generated by rocket launches are investigated. During the rocket passage, time rate change of total electron content (rTEC) enhancement with the V-shape shock wave signature is commonly observed, followed by acoustic wave disturbances and region of negative rTEC centered along the trajectory. Ten to fifteen min after the rocket passage, delayed disturbance waves appeared and propagated along direction normal to the V-shape wavefronts. These observation features appeared most prominently in the 2016 North Korea rocket launch showing a very distinct V-shape rTEC enhancement over enormous areas along the southeast flight trajectory despite that it was also appeared in the 2009 North Korea rocket launch with the eastward flight trajectory. Numerical simulations using the physical-based nonlinear and nonhydrostatic coupled model of neutral atmosphere and ionosphere reproduce promised results in qualitative agreement with the characteristics of ionospheric disturbance waves observed in the 2009 event by considering the released energy of the rocket exhaust as the disturbance source. Simulations reproduce the shock wave signature of electron density enhancement, acoustic wave disturbances, the electron density depletion due to the rocket-induced pressure bulge, and the delayed disturbance waves. The pressure bulge results in outward neutral wind flows carrying neutrals and plasma away from it and leading to electron density depletions. Simulations further show, for the first time, that the delayed disturbance waves are produced by the surface reflection of the earlier arrival acoustic wave disturbances.
Haan, de J.E.S.; Shoeb, M.A.; Lopes Ferreira, H.M.; Kling, W.L.
2013-01-01
Variability and predictability constraints of wind hinder the cost-efficient integration of wind power generation into power markets. Within the framework of EIT KIC INNOENERGY Offwindtech project, a ‘Market Value’ tool is developed. Here, the market value of wind power generation can be assessed
Fernández, Cristina; Vega, José A
2018-05-04
Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling. Copyright © 2018 Elsevier Inc. All rights reserved.
Prediction of wind power potential by wind speed probability distribution in a hilly terrain near Bh
Energy Technology Data Exchange (ETDEWEB)
Ahmed, Siraj; Diwakar, Nilesh
2010-09-15
Daily wind speed data in metre per second and its direction of flow in degree were recorded from of the India Meteorological Department for a site near the Bhopal Airport for the period of eleven years. The influence of roughness of the terrain, obstacles and topography in terms of contour for the area were also taken into consideration. These data were analysed using WAsP programme and regional wind climate of the area was determined. It is seen from the analysis of the wind speed data and keeping the topographical variation of terrain, exploitable wind speed is experienced at 50 m.
Energy Technology Data Exchange (ETDEWEB)
NONE
2009-06-15
The authors report a study which aimed at exploiting and deepening the results of a 2001 survey on visual and sound disturbances caused by wind turbines in Sigean (Aude), at identifying all the attitudes and opinions with respect with wind energy, and at assessing the different characteristics of a wind farm (height, localization, and so on). A survey has been performed on four sites located in different French regions. The authors discuss the social-demographic characteristics of the population samples, the global opinion on wind energy, and the opinion of the people on wind turbines located in their neighbourhood. They propose an estimation of benefits and damages related to the vicinity of wind turbines. By applying a method of choice experiments, they reveal the preferences of residents
Time Series Model of Wind Speed for Multi Wind Turbines based on Mixed Copula
Directory of Open Access Journals (Sweden)
Nie Dan
2016-01-01
Full Text Available Because wind power is intermittent, random and so on, large scale grid will directly affect the safe and stable operation of power grid. In order to make a quantitative study on the characteristics of the wind speed of wind turbine, the wind speed time series model of the multi wind turbine generator is constructed by using the mixed Copula-ARMA function in this paper, and a numerical example is also given. The research results show that the model can effectively predict the wind speed, ensure the efficient operation of the wind turbine, and provide theoretical basis for the stability of wind power grid connected operation.
Wind class sampling of satellite SAR imagery for offshore wind resource mapping
DEFF Research Database (Denmark)
Badger, Merete; Badger, Jake; Nielsen, Morten
2010-01-01
developed for mesoscale modeling of wind resources. Its performance in connection with sampling of SAR scenes is tested against two sets of random SAR samples and meteorological observations at three sites in the North Sea during 2005–08. Predictions of the mean wind speed and the Weibull scale parameter......High-resolution wind fields retrieved from satellite synthetic aperture radar (SAR) imagery are combined for mapping of wind resources offshore where site measurements are costly and sparse. A new sampling strategy for the SAR scenes is introduced, based on a method for statistical......-dynamical downscaling of large-scale wind conditions using a set of wind classes that describe representative wind situations. One or more SAR scenes are then selected to represent each wind class and the classes are weighted according to their frequency of occurrence. The wind class methodology was originally...
The design of wind turbine for electrical power generation in Malaysian wind characteristics
International Nuclear Information System (INIS)
Abas Ab Wahab; Chong Wen Thong
2000-01-01
The paper describes the study of a wind turbine for electrical power generation in Malaysia wind characteristics. In this research, the wind turbine is designs based on the local wind characteristics and tries to avoid the problems faced in the past (turbine design, access, manpower and technical). The new wind turbine rotor design for a medium speed wind speed turbine utilises the concept of open-close type of horizontal axis (up-wind) wind turbine is intended to widen the optimum performance range for electrical generation in Malaysia wind characteristics. The wind turbine has been designed to cut-in at a lower speed, and to provide the rotation speed that high enough to run a generator. The analysis and design of new low speed wind turbine blades and open-close turbine rotor and prediction of turbine performance are being detailed in this paper. (Author)
Powering Up With Space-Time Wind Forecasting
Hering, Amanda S.
2010-03-01
The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality, short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, that is, highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an offsite location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting wind at other locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each models predictions. © 2010 American Statistical Association.
Powering Up With Space-Time Wind Forecasting
Hering, Amanda S.; Genton, Marc G.
2010-01-01
The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality, short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, that is, highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an offsite location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting wind at other locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each models predictions. © 2010 American Statistical Association.
Power system stabilizer control for wind power to enhance power system stability
Domínguez García, José Luís; Gomis Bellmunt, Oriol; Bianchi, Fernando Daniel; Sumper, Andreas
2011-01-01
The paper presents a small signal stability analysis for power systems with wind farm interaction. Power systems have damping oscillation modes that can be excited by disturbance or fault in the grid. The power converters of the wind farms can be used to reduce these oscillations and make the system more stable. These ideas are explored to design a power system stabilized (PSS) for a network with conventional generators and a wind farm in order to increase the damping of the oscillation...
Assessing the responses of coastal cetaceans to the construction of offshore wind turbines.
Thompson, Paul M; Lusseau, David; Barton, Tim; Simmons, Dave; Rusin, Jan; Bailey, Helen
2010-08-01
The expansion of offshore renewables has raised concerns over potential disturbance to coastal cetaceans. In this study, we used passive acoustic monitoring to assess whether cetaceans responded to pile-driving noise during the installation of two 5MW offshore wind turbines off NE Scotland in 2006. Monitoring was carried out at both the turbine site and a control site in 2005, 2006 and 2007. Harbour porpoises occurred regularly around the turbine site in all years, but there was some evidence that porpoises did respond to disturbance from installation activities. We use these findings to highlight how uncertainty over cetacean distribution and the scale of disturbance effects constrains opportunities for B-A-C-I studies. We explore alternative approaches to assessing the impact of offshore wind farm upon cetaceans, and make recommendations for the research and monitoring that will be required to underpin future developments. Copyright 2010 Elsevier Ltd. All rights reserved.
Costs of the grid connection of wind turbines
Energy Technology Data Exchange (ETDEWEB)
Siden, G [Halmstad Univ. (Sweden)
1996-12-31
The costs of the grid connection of wind turbines in Sweden have until now been about 5 % of the total investments, provided that the distance of the connection cable is limited. Now the grid will soon be filled locally and it will be necessary to strengthen it. The costs for this can also be about 5 %, and the total cost about 10 %. Improvements in the electrical systems of the wind turbines and the connection technique can give less disturbance in the grid and diminish the costs. It is important to agree on how to share the costs for strengthening the grid. Otherwise, it can become an obstacle when building new wind turbines. (author)
Costs of the grid connection of wind turbines
International Nuclear Information System (INIS)
Siden, G.
1995-01-01
The costs of the grid connection of wind turbines in Sweden have until now been about 5 % of the total investments, provided that the distance of the connection cable is limited. Now the grid will soon be filled locally and it will be necessary to strengthen it. The costs for this can also be about 5 %, and the total cost about 10 %. Improvements in the electrical systems of the wind turbines and the connection technique can give less disturbance in the grid and diminish the costs. It is important to agree on how to share the costs for strengthening the grid. Otherwise, it can become an obstacle when building new wind turbines. (author)
Costs of the grid connection of wind turbines
Energy Technology Data Exchange (ETDEWEB)
Siden, G. [Halmstad Univ. (Sweden)
1995-12-31
The costs of the grid connection of wind turbines in Sweden have until now been about 5 % of the total investments, provided that the distance of the connection cable is limited. Now the grid will soon be filled locally and it will be necessary to strengthen it. The costs for this can also be about 5 %, and the total cost about 10 %. Improvements in the electrical systems of the wind turbines and the connection technique can give less disturbance in the grid and diminish the costs. It is important to agree on how to share the costs for strengthening the grid. Otherwise, it can become an obstacle when building new wind turbines. (author)
Harmonics in a Wind Power Plant: Preprint
Energy Technology Data Exchange (ETDEWEB)
Preciado, V.; Madrigal, M.; Muljadi, E.; Gevorgian, V.
2015-04-02
Wind power generation has been growing at a very fast pace for the past decade, and its influence and impact on the electric power grid is significant. As in a conventional power plant, a wind power plant (WPP) must ensure that the quality of the power being delivered to the grid is excellent. At the same time, the wind turbine should be able to operate immune to small disturbances coming from the grid. Harmonics are one of the more common power quality issues presented by large WPPs because of the high switching frequency of the power converters and the possible nonlinear behavior from electric machines (generator, transformer, reactors) within a power plant. This paper presents a summary of the most important issues related to harmonics in WPPs and discusses practical experiences with actual Type 1 and Type 3 wind turbines in two WPPs.
Tracking a major interplanetary disturbance
International Nuclear Information System (INIS)
Tappin, S.J.; Hewish, A.; Gapper, G.R.
1983-01-01
The severe geomagnetic storm which occurred during 27-29 August 1978 was remarkable because it arrived unexpectedly and was not related to a solar flare or long-lived coronal hole. Observations on 900 celestial radio sources show that the storm was associated with a large-scale region causing enhanced interplanetary scintillation which enveloped the Earth at the same time. The disturbance was first detected on 26 August, when the outer boundary had reached a distance of about 0.8 a.u. from the Sun and it was tracked until 30 August. The enhancement was followed by a fast solar wind stream and its shape suggests that it was a compression zone caused by the birth of the stream. (author)
Directory of Open Access Journals (Sweden)
Kai Ni
2017-05-01
Full Text Available This paper investigates the performance of a fault-tolerant four-switch three-phase (FSTP grid-side converter (GSC in a doubly-fed induction generator-based wind turbine (DFIG-WT. The space vector pulse width modulation (SVPWM technique is simplified and unified duty ratios are used for controlling the FSTP GSC. Steady DC-bus voltage, sinusoidal three-phase grid currents and unity power factor are obtained. In addition, the balance of capacitor voltages is accomplished based on the analysis of current flows at the midpoint of DC bus in different operational modes. Besides, external disturbances such as fluctuating wind speed and grid voltage sag are considered to test its fault-tolerant ability. Furthermore, the effects of fluctuating wind speed on the performance of DFIG-WT system are explained according to an approximate expression of the turbine torque. The performance of the proposed FSTP GSC is simulated in Matlab/Simulink 2016a based on a detailed 1.5 MW DFIG-WT Simulink model. Experiments are carried out on a 2 kW platform by using a discrete signal processor (DSP TMS320F28335 controller to validate the reliability of DFIG-WT for the cases with step change of the stator active power and grid voltage sag, respectively.
Implementing wind forecasting at a utility
Energy Technology Data Exchange (ETDEWEB)
Landberg, L.; Hansen, M.A.; Vesterager, K.; Bergstroem, W.
1997-03-01
This report describes a project - funded by the Danish Ministry of Energy and the Environment - that has as its aim to implement prediction of the power produced by wind farms in the daily planning at the Danish utility ELKRAFT. The predictions are generated from forecasts from HIRLAM (HIgh Resolution Limited Area Model) of the Danish Meteorological Institute. These predictions are then made valid at individual sites (wind farms) by applying either a matrix generated by the sub-models of WA{sup s}P (Wind Atlas Application and Analysis Program) or by use of a Kalman filter. In the project 17 wind farms have been selected for study. The farms are located on the Zealand and Bornholm islands and all belonging to the Danish utility ELKRAFT. (au) 10 tabs., 65 ills., 14 refs.
Energy Technology Data Exchange (ETDEWEB)
Pedersen, Eja [Halmstad Univ., Halmstad (Sweden). School of Business and Engineering; Persson-Waye, K [Goeteborg Univ., Goeteborg (Sweden). Dept. of Environmental Medicine
2002-02-01
To evaluate the occurrence of annoyance from wind turbines, a study was performed in Laholm in May 2000. The aim was to obtain dose response relationships between calculated sound levels and noise annoyance and appropriate sound description as well as analysing the influence of other variables on noise annoyance. A questionnaire survey was performed in 6 areas comprising 16 wind turbines, of which 14 had an effect of 600 kW. The purpose of the study was masked. Among questions on living conditions in the countryside, questions directly related to wind turbines were included. The study population (n=518) comprised one randomly selected subject between the ages of 18 to 75 years in each household living within a calculated wind turbine sound level of 25 to 40 dBA. The response rate was 68.7% (n=356). Calculated distributions of A-weighted sound level were performed for each area and plotted on geographical maps in 2.5 dBA steps. Each dwelling could thus be given a sound level within an interval of 2.5 dBA. The most frequently occurring source of noise annoyance was noise from rotor blades. The proportions of respondents annoyed by noise increased with calculated sound level. Among respondents exposed to sound levels of 35.0-37.5 dBA, 43% responded themselves to be rather or much annoyed. A-weighted sound level was only one variable explaining annoyance. Annoyance was correlated to a larger extent by the intrusiveness of the sound character swishing. Noise annoyance was interrelated to the respondents' opinion of the visual impact of wind turbines, while attitude towards wind power in general had no greater influence. Disturbance of spoilt view was reported to a similar degree as noise disturbance. Further investigations are needed to clarify factors of importance for the disturbance of view. All the wind turbines in the study had constant rotation speed. The greater wind turbines that are now erected often have variable speed, which may lead to a sound comprising
Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data
Directory of Open Access Journals (Sweden)
L. Cai
2010-02-01
Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect
Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data
Directory of Open Access Journals (Sweden)
L. Cai
2010-02-01
Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring
Mitigation of mechanical loads of NREL 5MW wind turbine tower
International Nuclear Information System (INIS)
Nam, Yoonsu; Im, Chang Hee
2012-01-01
As the size of a wind turbine increases, the mechanical structure has to have an increasing mechanical stiffness that is sufficient to withstand mechanical fatigue loads over a lifespan of more than 20 years. However, this leads to a heavier mechanical design, which means a high material cost during wind turbine manufacturing. Therefore, lightweight design of a wind turbine is an important design constraint. Usually, a lightweight mechanical structure has low damping. Therefore, if it is subjected to a disturbance, it will oscillate continuously. This study deals with the active damping control of a wind turbine tower. An algorithm that mitigates the mechanical loads of a wind turbine tower is introduced. The effectiveness of this algorithm is verified through a numerical simulation using GH Bladed, which is a commercial aero elastic code for wind turbines
Disturbance, neutral theory, and patterns of beta diversity in soil communities.
Maaß, Stefanie; Migliorini, Massimo; Rillig, Matthias C; Caruso, Tancredi
2014-12-01
Beta diversity describes how local communities within an area or region differ in species composition/abundance. There have been attempts to use changes in beta diversity as a biotic indicator of disturbance, but lack of theory and methodological caveats have hampered progress. We here propose that the neutral theory of biodiversity plus the definition of beta diversity as the total variance of a community matrix provide a suitable, novel, starting point for ecological applications. Observed levels of beta diversity (BD) can be compared to neutral predictions with three possible outcomes: Observed BD equals neutral prediction or is larger (divergence) or smaller (convergence) than the neutral prediction. Disturbance might lead to either divergence or convergence, depending on type and strength. We here apply these ideas to datasets collected on oribatid mites (a key, very diverse soil taxon) under several regimes of disturbances. When disturbance is expected to increase the heterogeneity of soil spatial properties or the sampling strategy encompassed a range of diverging environmental conditions, we observed diverging assemblages. On the contrary, we observed patterns consistent with neutrality when disturbance could determine homogenization of soil properties in space or the sampling strategy encompassed fairly homogeneous areas. With our method, spatial and temporal changes in beta diversity can be directly and easily monitored to detect significant changes in community dynamics, although the method itself cannot inform on underlying mechanisms. However, human-driven disturbances and the spatial scales at which they operate are usually known. In this case, our approach allows the formulation of testable predictions in terms of expected changes in beta diversity, thereby offering a promising monitoring tool.
Nurtrimarini Karim, Andi; Mawar Said, Sri; Chaerah Gunadin, Indar; Darusman B, Mustadir
2018-03-01
This paper presents a rotor angle analysis when transient disturbance occurs when wind turbines enter the southern Sulawesi electrical interconnection system (Sulbagsel) both without and with the addition of a Power Stabilizer (PSS) control device. Time domain simulation (TDS) method is used to analyze the rotor angle deviation (δ) and rotor angle velocity (ω). A total of 44 buses, 47 lines, 6 transformers, 15 generators and 34 loads were modeled for analysis after the inclusion of large-scale wind turbines in the Sidrap and Jeneponto areas. The simulation and computation results show the addition of PSS devices to the system when transient disturbance occurs when the winds turbine entering the Sulbagsel electrical system is able to dampen and improve the rotor angle deviation (δ) and the rotor angle velocity (ω) towards better thus helping the system to continue operation at a new equilibrium point.
Modeling and analysis of solar wind generated contributions to the near-Earth magnetic field
DEFF Research Database (Denmark)
Vennerstrøm, Susanne; Moretto, T.; Rastatter, L.
2006-01-01
Solar wind generated magnetic disturbances are currently one of the major obstacles for improving the accuracy in the determination of the magnetic field due to sources internal to the Earth. In the present study a global MHD model of solar wind magnetosphere interaction is used to obtain...... a physically consistent, divergence-free model of ionospheric, field-aligned and magnetospheric currents in a realistic magnetospheric geometry. The magnetic field near the Earth due to these currents is analyzed by estimating and comparing the contributions from the various parts of the system, with the aim...... of identifying the most important aspects of the solar wind disturbances in an internal field modeling context. The contribution from the distant magnetospheric currents is found to consist of two, mainly opposing, contributions from respectively the dayside magnetopause currents and the cross-tail current...
Short time ahead wind power production forecast
International Nuclear Information System (INIS)
Sapronova, Alla; Meissner, Catherine; Mana, Matteo
2016-01-01
An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)
Short time ahead wind power production forecast
Sapronova, Alla; Meissner, Catherine; Mana, Matteo
2016-09-01
An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.
Effects of Capcitor Bank on Fault Ride Through Capibility of Induction Generator Based Wind Turbines
DEFF Research Database (Denmark)
Hu, Y; Chen, Zhe
2010-01-01
power system stability and supply security. Some existing wind turbines are still based on fixed speed induction generators, the effects of capacitor bank on such generators are discussed in this paper. The simulation study shows the capacitor bank may costeffectively improve the dynamic performance......Wind turbine installation is increasing rapidly. In some networks, wind power penetration is significantly high and the performance of wind turbine plays an important role in power system operation and control. Especially, the behavior of wind turbines during a power system disturbance would affect...
Prediction of high-energy (> 0.3 MeV) substorm-related magnetospheric particles
International Nuclear Information System (INIS)
Baker, D.N.; Belian, R.D.; Higbie, P.R.; Hones, E.W. Jr.
1979-01-01
Measurements both at 6.6 R/sub E/ and in the plasma sheet (greater than or equal to 18 R/sub E/) show that high energy substorm-accelerated particles occur preferentially when the solar wind speed (V/sub sw/) is high. Virtually no > 0.3 MeV protons, for example, are observed in association with substorms that occur when V/sub sw/ is 700 km/sec. These results suggest that realtime monitoring of interplanetary conditions could allow simple, effective prediction of high energy magnetospheric particle disturbances. 7 references
Lunsford-Avery, Jessica R; Gonçalves, Bruno da Silva Brandão; Brietzke, Elisa; Bressan, Rodrigo A; Gadelha, Ary; Auerbach, Randy P; Mittal, Vijay A
2017-11-01
Individuals with psychotic disorders experience disruptions to both the sleep and circadian components of the sleep/wake cycle. Recent evidence has supported a role of sleep disturbances in emerging psychosis. However, less is known about how circadian rhythm disruptions may relate to psychosis symptoms and prognosis for adolescents with clinical high-risk (CHR) syndromes. The present study examines circadian rest/activity rhythms in CHR and healthy control (HC) youth to clarify the relationships among circadian rhythm disturbance, psychosis symptoms, psychosocial functioning, and the longitudinal course of illness. Thirty-four CHR and 32 HC participants were administered a baseline evaluation, which included clinical interviews, 5days of actigraphy, and a sleep/activity diary. CHR (n=29) participants were re-administered clinical interviews at a 1-year follow-up assessment. Relative to HC, CHR youth exhibited more fragmented circadian rhythms and later onset of nocturnal rest. Circadian disturbances (fragmented rhythms, low daily activity) were associated with increased psychotic symptom severity among CHR participants at baseline. Circadian disruptions (lower daily activity, rhythms that were more fragmented and/or desynchronized with the light/dark cycle) also predicted severity of psychosis symptoms and psychosocial impairment at 1-year follow-up among CHR youth. Circadian rhythm disturbances may represent a potential vulnerability marker for emergence of psychosis, and thus, rest/activity rhythm stabilization has promise to inform early-identification and prevention/intervention strategies for CHR youth. Future studies with longer study designs are necessary to further examine circadian rhythms in the prodromal period and rates of conversion to psychosis among CHR teens. Copyright © 2017. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
Li Zhang
2017-12-01
Full Text Available Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN is proposed in this paper. The raw data are firstly processed by FIG to extract useful information from each time window. The extracted information is then used to construct a wavelet neural network (WNN prediction model. Furthermore, the structural parameters of WNN are optimized by chaotic particle swarm optimization (CPSO before it is used to predict the fluctuation range of the hotspot temperature. By analyzing the experimental data with four different prediction models, we find that the proposed method is more effective and is of guiding significance for the operation and maintenance of transformers.
Disturbance Driven Rainfall in O`ahu, Hawai`i (1990-2010)
Longman, R. J.; Elison Timm, O.; Giambelluca, T. W.; Kaiser, L.; Newman, A. J.; Arnold, J.; Clark, M. P.
2017-12-01
Trade wind orographic rainfall is the most prevalent synoptic weather pattern in Hawai`i and provides a year-round source of moisture to the windward areas across the Island chain. Significant contributions to total and extreme precipitation have also been linked to one of four atmospheric disturbance situations that include: cold fronts, Kona storms, upper-tropospheric disturbances (upper level lows), and tropical systems. The primary objective of this research is to determine how these disturbance types contribute to total wet-season rainfall (RF) on the Island of O`ahu, Hawai`i and to identify any significant changes in the frequency of occurrence and or the intensity of these events. Atmospheric fronts that occurred in the Hawai`i region (17-26°N, 150-165°W) were extracted from a global dataset and combined with a Kona low and upper level low dataset to create a daily categorical weather classification time series (1990-2010). Mean rainfall was extracted from gridded daily O`ahu RF maps. Results show that the difference between a wet and dry year is predominantly explained by the RF contributions from disturbance events (r2 = 0.57, p cold fronts that cross the Island. During the wettest season on record, disturbances accounted for 48% of the total RF, while during the driest season they accounted for only 6% of the total RF. The event-based RF analysis also compared the RF intensity in the absence of disturbance events with the average RF intensity on days when atmospheric fronts are present but do not cross the island. The results show that non-crossing fronts reduce the average RF intensity. A possible explanation is that these events are too far away to produce RF, but close enough to disrupt normal trade wind flow, thus limiting orographic RF on the island. This new event-based RF analysis has important implications for the projection of regional climate change in Hawai`i. Our results suggest that if storm tracks were to shift poleward, O`ahu wet season
DEFF Research Database (Denmark)
Alessandrini, Stefano; Sperati, Simone; Pinson, Pierre
2012-01-01
Short-term forecasting applied to wind energy is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty requires a constant effort to meet the needs of the national electrical systems and their operators. Regarding to this, the probabilistic approach...... calibration performed on the wind speed EPS members allows an improvement from an over-confident situation observable from the rank histograms (in which the measurements fell quite always outside the bounds of the probability distribution) to a consistent ensemble spread. After that it is possible to convert...... the data to wind energy: the spread calculated on wind power can then be used as an accuracy predictor due to its level of correlation with the deterministic WPF error. In this presentation we investigate the performances for both wind power and accuracy prediction of the new EPS used at the ECMWF, whose...
International Nuclear Information System (INIS)
Sarrias-Mena, Raúl; Fernández-Ramírez, Luis M.; García-Vázquez, Carlos Andrés; Jurado, Francisco
2014-01-01
Integrating energy storage systems (ESS) with wind turbines results to be an interesting option for improving the grid integration capability of wind energy. This paper presents and evaluates a wind hybrid system consisting of a 1.5 MW doubly-fed induction generator (DFIG) wind turbine and double battery-ultracapacitor ESS. Commercially available components are used in this wind hybrid system. A novel supervisory control system (SCS) is designed and implemented, which is responsible for setting the active and reactive power references for each component of the hybrid system. A fuzzy logic controller, taking into account the grid demand, power generation prediction, actual DFIG power generation and state-of-charge (SOC) of the ESSs, sets the active power references. The reactive power references are proportionally delivered to each element regarding their current limitations in the SCS. The appropriate control of the power converters allows each power source to achieve the operation defined by the SCS. The wind hybrid system and SCS are assessed by simulation under wind fluctuations, grid demand changes, and grid disturbances. Results show an improved performance in the overall response of the system with the implementation of the SCS. - Highlights: • We study a wind hybrid system based on DFIG wind turbine, battery and ultracapacitor. • A novel supervisory control system based on fuzzy logic is designed and implemented. • The control improves the system response under different operating conditions